Human Lanterns 人皮燈籠 (1982)

88 Films Blu-ray 2022

Ren pi deng long (Human Lanterns, 1982)

"I want to take your life this day!"

"My life was taken seven years ago. The person standing here now is merely a walking corpse."

Another rarely seen fight scene. This time from the Chinese drama, The Romance of the White Haired Maiden (1986)

That fight choreography is slick as hell.

Chen Kuan-Tai vs Johnny Wang Lung-Wei in The Master 背叛師門 (1980)

Crippled Avengers (1978)

BTS photos of Lau Kar-leung choreographing a fight scene between Chen Kuan-tai and Ti Lung from Blood Brothers/刺马 (1973)

Lo Mang and Chen Kuan-Tai battle in Human Lanterns (1982)

a o e i i er ai ei ao ou an en ang eng ong i ia iao ie iu ian in iang ing iong u ua uo uai ui uan un uang ueng ü üe üan ün a o e er ai ao ou an en ang eng yi ya yao ye you yan yin yang ying yong wu wa wo wai wei wan wen wang weng yu yue yuan yun b ba bo bai bei bao ban ben bang beng bi biao bie bian bin bing bu p pa po pai pei pao pou pan pen pang peng pi piao pie pian pin ping pu m ma mo me mai mei mao mou man men mang meng mi miao mie miu mian min ming mu f fa fo fei fou fan fen fang feng fu d da de dai dei dao dou dan den dang deng dong di diao die diu dian ding du duo dui duan dun t ta te tai tei tao tou tan tang teng tong ti tiao tie tian ting tu tuo tui tuan tun n na ne nai nei nao nou nan nen nang neng nong ni niao nie niu nian nin niang ning nu nuo nuan nü nüe l la le lai lei lao lou lan lang leng long li lia liao lie liu lian lin liang ling lu luo luan lun lü lüe g ga ge gai gei gao gou gan gen gang geng gong gu gua guo guai gui guan gun guang k ka ke kai kei kao kou kan ken kang keng kong ku kua kuo kuai kui kuan kun kuang h ha he hai hei hao hou han hen hang heng hong hu hua huo huai hui huan hun huang z za ze zi zai zei zao zou zan zen zang zeng zong zu zuo zui zuan zun c ca ce ci cai cao cou can cen cang ceng cong cu cuo cui cuan cun s sa se si sai sao sou san sen sang seng song su suo sui suan sun zh zha zhe zhi zhai zhei zhao zhou zhan zhen zhang zheng zhong zhu zhua zhuo zhuai zhui zhuan zhun zhuang ch cha che chi chai chao chou chan chen chang cheng chong chu chua chuo chuai chui chuan chun chuang sh sha she shi shai shei shao shou shan shen shang sheng shu shua shuo shuai shui shuan shun shuang r re ri rao rou ran ren rang reng rong ru rua ruo rui ruan run j ji jia jiao jie jiu jian jin jiang jing jiong ju jue juan jun q qi qia qiao qie qiu qian qin qiang qing qiong qu que quan qun x xi xia xiao xie xiu xian xin xiang xing xiong xu xue xuan xun

NAKU 🫵

List of Gods, most of which are no longer worshipped. via /r/atheism

List of Gods, most of which are no longer worshipped.

Middle-East

A, Adad, Adapa, Adrammelech, Aeon, Agasaya, Aglibol, Ahriman, Ahura Mazda, Ahurani, Ai-ada, Al-Lat, Aja, Aka, Alalu, Al-Lat, Amm, Al-Uzza (El-'Ozza or Han-Uzzai), An, Anahita, Anath (Anat), Anatu, Anbay, Anshar, Anu, Anunitu, An-Zu, Apsu, Aqhat, Ararat, Arinna, Asherali, Ashnan, Ashtoreth, Ashur, Astarte, Atar, Athirat, Athtart, Attis, Aya, Baal (Bel), Baalat (Ba'Alat), Baau, Basamum, Beelsamin, Belit-Seri, Beruth, Borak, Broxa, Caelestis, Cassios, Lebanon, Antilebanon, and Brathy, Chaos, Chemosh, Cotys, Cybele, Daena, Daevas, Dagon, Damkina, Dazimus, Derketo, Dhat-Badan, Dilmun, Dumuzi (Du'uzu), Duttur, Ea, El, Endukugga, Enki, Enlil, Ennugi, Eriskegal, Ereshkigal (Allatu), Eshara, Eshmun, Firanak, Fravashi, Gatamdug, Genea, Genos, Gestinanna, Gula, Hadad, Hannahanna, Hatti, Hea, Hiribi, The Houri, Humban, Innana, Ishkur, Ishtar, Ithm, Jamshid or Jamshyd, Jehovah, Jesus, Kabta, Kadi, Kamrusepas, Ki (Kiki), Kingu, Kolpia, Kothar-u-Khasis, Lahar, Marduk, Mari, Meni, Merodach, Misor, Moloch, Mot, Mushdama, Mylitta, Naamah, Nabu (Nebo), Nairyosangha, Nammu, Namtaru, Nanna, Nebo, Nergal, Nidaba, Ninhursag or Nintu, Ninlil, Ninsar, Nintur, Ninurta, Pa, Qadshu, Rapithwin, Resheph (Mikal or Mekal), Rimmon, Sadarnuna, Shahar, Shalim, Shamish, Shapshu, Sheger, Sin, Siris (Sirah), Taautos, Tammuz, Tanit, Taru, Tasimmet, Telipinu, Tiamat, Tishtrya, Tsehub, Utnapishtim, Utu, Wurusemu, Yam, Yarih (Yarikh), Yima, Zaba, Zababa, Zam, Zanahary (Zanaharibe), Zarpandit, Zarathustra, Zatavu, Zazavavindrano, Ziusudra, Zu (Imdugud), Zurvan

China:

Ba, Caishen, Chang Fei, Chang Hsien, Chang Pan, Ch'ang Tsai, Chao san-Niang, Chao T'eng-k'ang, Chen Kao, Ch'eng Huang, Cheng San-Kung, Cheng Yuan-ho, Chi Po, Chien-Ti, Chih Jih, Chih Nii, Chih Nu, Ch'ih Sung-tzu, Ching Ling Tzu, Ch'ing Lung, Chin-hua Niang-niang, Chio Yuan-Tzu, Chou Wang, Chu Niao, Chu Ying, Chuang-Mu, Chu-jung, Chun T'i, Ch'ung Ling-yu, Chung Liu, Chung-kuei, Chung-li Ch'üan, Di Jun, Fan K'uei, Fei Lien, Feng Pho-Pho, Fengbo, Fu Hsing, Fu-Hsi, Fu-Pao, Gaomei, Guan Di, Hao Ch'iu, Heng-o, Ho Po (Ping-I), Hou Chi, Hou T'u, Hsi Ling-su, Hsi Shih, Hsi Wang Mu, Hsiao Wu, Hsieh T'ien-chun, Hsien Nung, Hsi-shen, Hsu Ch'ang, Hsuan Wen-hua, Huang Ti, Huang T'ing, Huo Pu, Hu-Shen, Jen An, Jizo Bosatsu, Keng Yen-cheng, King Wan, Ko Hsien-Weng, Kuan Ti, Kuan Ti, Kuei-ku Tzu, Kuo Tzu-i, Lai Cho, Lao Lang, Lei Kung, Lei Tsu, Li Lao-chun, Li Tien, Liu Meng, Liu Pei, Lo Shen, Lo Yu, Lo-Tsu Ta-Hsien, Lu Hsing, Lung Yen, Lu-pan, Ma-Ku, Mang Chin-i, Mang Shen, Mao Meng, Men Shen, Miao Hu, Mi-lo Fo, Ming Shang, Nan-chi Hsien-weng, Niu Wang, Nu Wa, Nu-kua, Pa, Pa Cha, Pai Chung, Pai Liu-Fang, Pai Yu, P'an Niang, P'an-Chin-Lien, Pao Yuan-ch'uan, Phan Ku, P'i Chia-Ma, Pien Ho, San Kuan, Sao-ch'ing Niang, Sarudahiko, Shang Chien, Shang Ti, She chi, Shen Hsui-Chih, Shen Nung, Sheng Mu, Shih Liang, Shiu Fang, Shou-lao, Shun I Fu-jen, Sien-Tsang, Ssu-ma Hsiang-ju, Sun Pin, Sun Ssu-miao, Sung-Chiang, Tan Chu, T'ang Ming Huang, Tao Kung, T'ien Fei, Tien Hou, Tien Mu, Ti-tsang, Tsai Shen, Ts'an Nu, Ts'ang Chien, Tsao Chun, Tsao-Wang, T'shai-Shen, Tung Chun, T'ung Chung-chung, T'ung Lai-yu, Tung Lu, T'ung Ming, Tzu-ku Shen, Wa, Wang Ta-hsien, Wang-Mu-Niang-Niang, Weiwobo, Wen-ch'ang, Wu-tai Yuan-shuai, Xi Hou, Xi Wangmu, Xiu Wenyin, Yanwang, Yaoji, Yen-lo, Yen-Lo-Wang, Yi, Yu, Yu Ch'iang, Yu Huang, Yun-T'ung, Yu-Tzu, Zaoshen, Zhang Xi, , Zhinü, , Zhongguei, , Zigu Shen, , Zisun, Ch'ang-O

Slavic:

Aba-khatun, Aigiarm, Ajysyt, Alkonost, Almoshi, Altan-Telgey, Ama, Anapel, As-ava, Ausaitis, Austeja, Ayt'ar, Baba Yaga (Jezi Baba), Belobog (Belun), Boldogasszony, Breksta, Bugady Musun, Chernobog (Crnobog, Czarnobog, Czerneboch, Cernobog), Cinei-new, Colleda (Koliada), Cuvto-ava, Dali, Darzu-mate, Dazhbog, Debena, Devana, Diiwica (Dilwica), Doda (Dodola), Dolya, Dragoni, Dugnai, Dunne Enin, Edji, Elena, Erce, Etugen, Falvara, The Fates, The Fatit, Gabija, Ganiklis, Giltine, Hotogov Mailgan, Hov-ava, Iarila, Isten, Ja-neb'a, Jedza, Joda-mate, Kaldas, Kaltes, Keretkun, Khadau, Khursun (Khors), Kostrubonko, Kovas, Krumine, Kupala, Kupalo, Laima, Leshy, Marina, Marzana, Matergabiae, Mat Syra Zemlya, Medeine, Menu (Menulis), Mir-Susne-Khum, Myesyats, Nastasija, (Russia) Goddess of sleep., Nelaima, Norov, Numi-Tarem, Nyia, Ora, Ot, Patollo, Patrimpas, Pereplut, Perkuno, Perun, Pikuolis, Pilnytis, Piluitus, Potrimpo, Puskaitis, Rod, Rugevit, Rultennin, Rusalki, Sakhadai-Noin, Saule, Semargl, Stribog, Sudjaje, Svantovit (Svantevit, Svitovyd), Svarazic (Svarozic, Svarogich), Tengri, Tñairgin, Triglav, Ulgen (Ulgan, Ülgön), Veles (Volos), Vesna, Xatel-Ekwa, Xoli-Kaltes, Yamm, Yarilo, Yarovit, Ynakhsyt, Zaria, Zeme mate, Zemyna, Ziva (Siva), Zizilia, Zonget, Zorya, Zvoruna, Zvezda Dennitsa, Zywie

Hindu

Aditi, Adityas, Ambika, Ananta (Shesha), Annapurna (Annapatni), Aruna, Ashvins, Balarama, Bhairavi, Brahma, Buddha, Dakini, Devi, Dharma, Dhisana, Durga, Dyaus, Ganesa (Ganesha), Ganga (Ganges), Garuda, Gauri, Gopis, Hanuman, Hari-Hara, Hulka Devi, Jagganath, Jyeshtha, Kama, Karttikeya, Krishna, Krtya, Kubera, Kubjika, Lakshmi or Laksmi, Manasha, Manu, Maya, Meru, Nagas, Nandi, Naraka, Nataraja, Nirriti, Parjanya, Parvati, Paurnamasi, Prithivi, Purusha, Radha, Rati, Ratri, Rudra, Sanjna, Sati, Shashti, Shatala, Sitala (Satala), Skanda, Sunrta, Surya, Svasti-devi, Tvashtar, Uma, Urjani, Vach, Varuna, Vayu, Vishnu (Avatars of Vishnu: Matsya; Kurma; Varaha; Narasinha; Vamana; Parasurama; Rama; Krishna; Buddha; Kalki), Vishvakarman, Yama, Sraddha

Japan: Aji-Suki-Taka-Hi-Kone, Ama no Uzume, Ama-terasu, Amatsu Mikaboshi, Benten (Benzai-Ten), Bishamon, Chimata-No-Kami, Chup-Kamui, Daikoku, Ebisu, Emma-O, Fudo, Fuji, Fukurokuju, Gekka-O, Hachiman, Hettsui-No-Kami, Ho-Masubi, Hotei, Inari, Izanagi and Izanami, Jizo Bosatsu, Jurojin, Kagutsuchi, Kamado-No-Kami, Kami, Kawa-No-Kami, Kaya-Nu-Hima, Kishijoten, Kishi-Mojin, Kunitokotatchi, Marici, Monju-Bosatsu, Nai-No-Kami, No-Il Ja-Dae, O-Kuni-Nushi, Omoigane, Raiden, Shine-Tsu-Hiko, Shoten, Susa-no-wo, Tajika-no-mikoto, Tsuki-yomi, Uka no Mitanna, Uke-mochi, Uso-dori, Uzume, Wakahirume, Yainato-Hnneno-Mikoi, Yama-No-Kami, Yama-no-Karni, Yaya-Zakurai, Yuki-Onne

India

Agni, Ammavaru, Asuras, Banka-Mundi, Brihaspati, Budhi Pallien, Candi, Challalamma, Chinnintamma, Devas, Dyaush, Gauri-Sankar, Grhadevi, Gujeswari, Indra, Kali, Lohasur Devi, Mayavel, Mitra, Prajapati, Puchan, Purandhi, Rakshas, Rudrani, Rumina, Samundra, Sarasvati, Savitar, Siva (Shiva), Soma, Sura, Surabhi, Tulsi, Ushas, Vata, Visvamitra, Vivasvat, Vritra, Waghai Devi, Yaparamma, Yayu, Zumiang Nui, Diti

Other Asian: Dewi Shri, Po Yan Dari, Shuzanghu, Antaboga, Yakushi Nyorai, Mulhalmoni, Tankun, Yondung Halmoni, Aryong Jong, Quan Yin , Tengri, Uminai-gami, Kamado-No-Kami, Kunitokotatchi, Giri Devi, Dewi Nawang Sasih, Brag-srin-mo, Samanta-Bhadra, Sangs-rgyas-mkhá, Sengdroma, Sgeg-mo-ma, Tho-og, Ui Tango, Yum-chen-mo, Zas-ster-ma-dmar-mo, Chandra, Dyaus, Ratri, Rodasi, Vayu, Au-Co

African Gods, Demigods and First Men:

Abassi , Abuk , Adu Ogyinae , Agé , Agwe , Aida Wedo , Ajalamo, Aje, Ajok, Akonadi, Akongo, Akuj, Amma, Anansi, Asase Yaa, Ashiakle, Atai , Ayaba, Aziri, Baatsi, Bayanni, Bele Alua, Bomo rambi, Bosumabla, Buk, Buku, Bumba, Bunzi, Buruku, Cagn, Candit, Cghene, Coti, Damballah-Wedo, Dan, Deng, Domfe, Dongo, Edinkira, Efé, Egungun-oya, Eka Abassi, Elephant Girl Mbombe, Emayian, Enekpe, En-Kai, Eseasar, Eshu, Esu, Fa, Faran, Faro, Fatouma, Fidi Mukullu, Fon, Gleti, Gonzuole, Gû, Gua, Gulu, Gunab, Hammadi, Hêbiesso, Iku, Ilankaka, Imana, Iruwa, Isaywa, Juok, Kazooba, Khakaba, Khonvum, Kibuka, Kintu, Lebé, Leza, Libanza, Lituolone, Loko, Marwe, Massim Biambe, Mawu-Lisa (Leza), Mboze, Mebeli, Minepa, Moombi, Mukameiguru, Mukasa, Muluku, Mulungu, Mwambu, Nai, Nambi, Nana Buluku, Nanan-Bouclou, Nenaunir, Ng Ai, Nyaliep, Nyambé, Nyankopon, Nyasaye, Nzame, Oboto, Obumo, Odudua-Orishala, Ogun, Olokun, Olorun, Orisha Nla, Orunmila, Osanyin, Oshe, Osun, Oya, Phebele, Pokot-Suk, Ralubumbha, Rugaba, Ruhanga, Ryangombe, Sagbata, Shagpona, Shango, Sopona, Tano, Thixo, Tilo, Tokoloshi, Tsui, Tsui'goab, Umvelinqangi, Unkulunkulu, Utixo, Wak, Wamara, Wantu Su, Wele, Were, Woto, Xevioso, Yangombi, Yemonja, Ymoa, Ymoja, Yoruba, Zambi, Zanahary , Zinkibaru

Australian Gods, Goddesses and Places in the Dreamtime:

Alinga, Anjea, Apunga, Arahuta, Ariki, Arohirohi, Bamapana, Banaitja, Bara, Barraiya, Biame, Bila, Boaliri, Bobbi-bobbi, Bunbulama, Bunjil, Cunnembeille, Daramulum, Dilga, Djanggawul Sisters, Eingana, Erathipa, Gidja , Gnowee, Haumia, Hine Titama, Ingridi, Julana, Julunggul, Junkgowa, Karora, Kunapipi-Kalwadi-Kadjara, Lia, Madalait, Makara, Nabudi, Palpinkalare, Papa, Rangi, Rongo, Tane, Tangaroa, Tawhiri-ma-tea, Tomituka, Tu, Ungamilia, Walo, Waramurungundi, Wati Kutjarra, Wawalag Sisters, Wuluwaid, Wuragag, Wuriupranili, Wurrunna, Yhi

Buddhism, Gods and Relatives of God:

Aizen-Myoo, Ajima,Dai-itoku-Myoo, Fudo-Myoo, Gozanze-Myoo, Gundari-Myoo, Hariti, Kongo-Myoo, Kujaku-Myoo, Ni-O

Carribean: Gods, Monsters and Vodun Spirits

Agaman Nibo , Agwe, Agweta, Ah Uaynih, Aida Wedo , Atabei , Ayida , Ayizan, Azacca, Baron Samedi, Ulrich, Ellegua, Ogun, Ochosi, Chango, Itaba, Amelia, Christalline, Clairmé, Clairmeziné, Coatrischie, Damballah , Emanjah, Erzuli, Erzulie, Ezili, Ghede, Guabancex, Guabonito, Guamaonocon, Imanje, Karous, Laloue-diji, Legba, Loa, Loco, Maitresse Amelia , Mapiangueh, Marie-aimée, Marinette, Mombu, Marassa, Nana Buruku, Oba, Obtala, Ochu, Ochumare, Oddudua, Ogoun, Olokum, Olosa, Oshun, Oya, Philomena, Sirêne, The Diablesse, Itaba, Tsilah, Ursule, Vierge, Yemaya , Zaka

Celtic: Gods, Goddesses, Divine Kings and Pagan Saints

Abarta, Abna, Abnoba, Aine, Airetech,Akonadi, Amaethon, Ameathon, An Cailleach, Andraste, Antenociticus, Aranrhod, Arawn, Arianrod, Artio, Badb,Balor, Banbha, Becuma, Belatucadros, Belatu-Cadros, Belenus, Beli,Belimawr, Belinus, Bendigeidfran, Bile, Blathnat, Blodeuwedd, Boann, Bodus,Bormanus, Borvo, Bran, Branwen, Bres, Brigid, Brigit, Caridwen, Carpantus,Cathbadh, Cecht, Cernach, Cernunnos, Cliodna, Cocidius, Conchobar, Condatis, Cormac,Coronus,Cosunea, Coventina, Crarus,Creidhne, Creirwy, Cu Chulainn, Cu roi, Cuda, Cuill,Cyhiraeth,Dagda, Damona, Dana, Danu, D'Aulnoy,Dea Artio, Deirdre , Dewi, Dian, Diancecht, Dis Pater, Donn, Dwyn, Dylan, Dywel,Efnisien, Elatha, Epona, Eriu, Esos, Esus, Eurymedon,Fedelma, Fergus, Finn, Fodla, Goewyn, Gog, Goibhniu, Govannon , Grainne, Greine,Gwydion, Gwynn ap Nudd, Herne, Hu'Gadarn, Keltoi,Keridwen, Kernunnos,Ler, Lir, Lleu Llaw Gyffes, Lludd, Llyr, Llywy, Luchta, Lug, Lugh,Lugus, Mabinogion,Mabon, Mac Da Tho, Macha, Magog, Manannan, Manawydan, Maponos, Math, Math Ap Mathonwy, Medb, Moccos,Modron, Mogons, Morrig, Morrigan, Nabon,Nantosuelta, Naoise, Nechtan, Nedoledius,Nehalennia, Nemhain, Net,Nisien, Nodens, Noisi, Nuada, Nwywre,Oengus, Ogma, Ogmios, Oisin, Pach,Partholon, Penard Dun, Pryderi, Pwyll, Rhiannon, Rosmerta, Samhain, Segidaiacus, Sirona, Sucellus, Sulis, Taliesin, Taranis, Teutates, The Horned One,The Hunt, Treveni,Tyne, Urien, Ursula of the Silver Host, Vellaunus, Vitiris, White Lady

Egyptian: Gods, Gods Incarnate and Personified Divine Forces:

Amaunet, Amen, Amon, Amun, Anat, Anqet, Antaios, Anubis, Anuket, Apep, Apis, Astarte, Aten, Aton, Atum, Bastet, Bat, Buto, Duamutef, Duamutef, Hapi, Har-pa-khered, Hathor, Hauhet, Heket, Horus, Huh, Imset, Isis, Kauket, Kebechsenef, Khensu, Khepri, Khnemu, Khnum, Khonsu, Kuk, Maahes, Ma'at, Mehen, Meretseger, Min, Mnewer, Mut, Naunet, Nefertem, Neith, Nekhbet, Nephthys, Nun, Nut, Osiris, Ptah, Ra , Re, Renenet, Sakhmet, Satet, Seb, Seker, Sekhmet, Serapis, Serket, Set, Seth, Shai, Shu, Shu, Sia, Sobek, Sokar, Tefnut, Tem, Thoth

Hellenes (Greek) Tradition (Gods, Demigods, Divine Bastards)

Acidalia, Aello, Aesculapius, Agathe, Agdistis, Ageleia, Aglauros, Agne, Agoraia, Agreia, Agreie, Agreiphontes, Agreus, Agrios, Agrotera, Aguieus, Aidoneus, Aigiokhos, Aigletes, Aigobolos, Ainia,Ainippe, Aithuia , Akesios, Akraia, Aktaios, Alalkomene, Alasiotas, Alcibie, Alcinoe, Alcippe, Alcis,Alea, Alexikakos, Aligena, Aliterios, Alkaia, Amaltheia, Ambidexter, Ambologera, Amynomene,Anaduomene, Anaea, Anax, Anaxilea, Androdameia,Andromache, Andromeda, Androphonos, Anosia, Antandre,Antania, Antheus, Anthroporraistes, Antianara, Antianeira, Antibrote, Antimache, Antimachos, Antiope,Antiopeia, Aoide, Apatouria, Aphneius, Aphrodite, Apollo, Apotropaios, Areia, Areia, Areion, Areopagite, Ares, Areto, Areximacha,Argus, Aridnus,Aristaios, Aristomache, Arkhegetes, Arktos, Arretos, Arsenothelys, Artemis, Asclepius, Asklepios, Aspheleios, Asteria, Astraeos , Athene, Auxites, Avaris, Axios, Axios Tauros,Bakcheios, Bakchos, Basileus, Basilis, Bassareus, Bauros, Boophis, Boreas , Botryophoros, Boukeros, Boulaia, Boulaios, Bremusa,Bromios, Byblis,Bythios, Caliope, Cedreatis, Celaneo, centaur, Cerberus, Charidotes, Charybdis, Chimera, Chloe, Chloris , Choreutes, Choroplekes, Chthonios, Clete, Clio, clotho,Clyemne, cockatrice, Crataeis, Custos, Cybebe, Cybele, Cyclops, Daphnaia, Daphnephoros, Deianeira, Deinomache, Delia, Delios, Delphic, Delphinios, Demeter, Dendrites, Derimacheia,Derinoe, Despoina, Dikerotes, Dimeter, Dimorphos, Dindymene, Dioktoros, Dionysos, Discordia, Dissotokos, Dithyrambos, Doris, Dryope,Echephyle,Echidna, Eiraphiotes, Ekstatophoros, Eleemon, Eleuthereus, Eleutherios, Ennosigaios, Enodia, Enodios, Enoplios, Enorches, Enualios, Eos , Epaine, Epidotes, Epikourios, Epipontia, Epitragidia, Epitumbidia, Erato, Ergane, Eribromios, Erigdoupos, Erinus, Eriobea, Eriounios, Eriphos, Eris, Eros,Euanthes, Euaster, Eubouleus, Euboulos, Euios, Eukhaitos, Eukleia, Eukles, Eumache, Eunemos, Euplois, Euros , Eurybe,Euryleia, Euterpe, Fates,Fortuna, Gaia, Gaieokhos, Galea, Gamelia, Gamelios, Gamostolos, Genetor, Genetullis, Geryon, Gethosynos, giants, Gigantophonos, Glaukopis, Gorgons, Gorgopis, Graiae, griffin, Gynaikothoinas, Gynnis, Hagisilaos, Hagnos, Haides, Harmothoe, harpy, Hegemone, Hegemonios, Hekate, Hekatos, Helios, Hellotis, Hephaistia, Hephaistos, Hera, Heraios, Herakles, Herkeios, Hermes, Heros Theos, Hersos, Hestia, Heteira, Hiksios, Hipp, Hippia, Hippios, Hippoi Athanatoi, Hippolyte, Hippolyte II,Hippomache,Hippothoe, Horkos, Hugieia, Hupatos, Hydra, Hypate, Hyperborean, Hypsipyle, Hypsistos, Iakchos, Iatros, Idaia, Invictus, Iphito,Ismenios, Ismenus,Itonia, Kabeiria, Kabeiroi, Kakia, Kallinikos, Kallipugos, Kallisti, Kappotas, Karneios, Karpophoros, Karytis, Kataibates, Katakhthonios, Kathatsios, Keladeine, Keraunos, Kerykes, Khalinitis, Khalkioikos, Kharmon, Khera, Khloe, Khlori,Khloris,Khruse, Khthonia, Khthonios, Kidaria, Kissobryos, Kissokomes, Kissos, Kitharodos, Kleidouchos, Kleoptoleme, Klymenos, Kore, Koruthalia, Korymbophoros, Kourotrophos, Kranaia, Kranaios, Krataiis, Kreousa, Kretogenes, Kriophoros, Kronides, Kronos,Kryphios, Ktesios, Kubebe, Kupris, Kuprogenes, Kurotrophos, Kuthereia, Kybele, Kydoime,Kynthia, Kyrios, Ladon, Lakinia, Lamia, Lampter, Laodoke, Laphria, Lenaios, Leukatas, Leukatas, Leukolenos, Leukophruene, Liknites, Limenia, Limnaios, Limnatis, Logios, Lokhia, Lousia, Loxias, Lukaios, Lukeios, Lyaios, Lygodesma, Lykopis, Lyseus, Lysippe, Maimaktes, Mainomenos, Majestas, Makar, Maleatas, Manikos, Mantis, Marpe, Marpesia, Medusa, Megale, Meilikhios, Melaina, Melainis, Melanaigis, Melanippe,Melete, Melousa, Melpomene, Melqart, Meses, Mimnousa, Minotaur, Mneme, Molpadia,Monogenes, Morpho, Morychos, Musagates, Musagetes, Nebrodes, Nephelegereta, Nereus,Nete, Nike, Nikephoros, Nomios, Nomius, Notos , Nyktelios, Nyktipolos, Nympheuomene, Nysios, Oiketor, Okyale, Okypous, Olumpios, Omadios, Ombrios, Orithia,Orius,Ortheia, Orthos, Ourania, Ourios, Paelemona, Paian, Pais, Palaios, Pallas, Pan Megas, Panakhais, Pandemos, Pandrosos, Pantariste, Parthenos, PAsianax, Pasiphaessa, Pater, Pater, Patroo s, Pegasus, Pelagia, Penthesilea, Perikionios, Persephone, Petraios, Phanes, Phanter, Phatria, Philios, Philippis, Philomeides, Phoebe, Phoebus, Phoenix, Phoibos, Phosphoros, Phratrios, Phutalmios, Physis, Pisto, Plouton, Polemusa,Poliakhos, Polias, Polieus, Polumetis, Polydektes, Polygethes, Polymnia, Polymorphos, Polyonomos, Porne, Poseidon, Potnia Khaos, Potnia Pheron, Promakhos, Pronoia, Propulaios, Propylaia, Proserpine, Prothoe, Protogonos, Prytaneia, Psychopompos, Puronia, Puthios, Pyrgomache, Python, Rhea, Sabazios, Salpinx, satyr, Saxanus, Scyleia,Scylla, sirens, Skeptouchos, Smintheus, Sophia, Sosipolis, Soter, Soteria, Sphinx, Staphylos, Sthenias, Sthenios, Strife, Summakhia, Sykites, Syzygia, Tallaios, Taureos, Taurokeros, Taurophagos, Tauropolos, Tauropon, Tecmessa, Teisipyte, Teleios, Telepyleia,Teletarches, Terpsichore, Thalestris, Thalia, The Dioskouroi, Theos, Theritas, Thermodosa, Thraso, Thyonidas, Thyrsophoros, Tmolene, Toxaris, Toxis, Toxophile,Trevia, Tricephalus, Trieterikos, Trigonos, Trismegestos, Tritogeneia, Tropaios, Trophonius,Tumborukhos, Tyche, Typhon, Urania, Valasca, Xanthippe, Xenios, Zagreus, Zathos, Zephryos , Zeus, Zeus Katakhthonios, Zoophoros Topana

Native American: Gods, Heroes, and Anthropomorphized Facets of Nature

Aakuluujjusi, Ab Kin zoc, Abaangui , Ababinili , Ac Yanto, Acan, Acat, Achiyalatopa , Acna, Acolmiztli, Acolnahuacatl, Acuecucyoticihuati, Adamisil Wedo, Adaox , Adekagagwaa , Adlet , Adlivun, Agloolik , Aguara , Ah Bolom Tzacab, Ah Cancum, Ah Chun Caan, Ah Chuy Kak, Ah Ciliz, Ah Cun Can, Ah Cuxtal, Ah hulneb, Ah Kin, Ah Kumix Uinicob, Ah Mun, Ah Muzencab, Ah Patnar Uinicob, Ah Peku, Ah Puch, Ah Tabai, Ah UincirDz'acab, Ah Uuc Ticab, Ah Wink-ir Masa, Ahau Chamahez, Ahau-Kin, Ahmakiq, Ahnt Alis Pok', Ahnt Kai', Aholi , Ahsonnutli , Ahuic, Ahulane, Aiauh, Aipaloovik , Ajbit, Ajilee , Ajtzak, Akbaalia , Akba-atatdia , Akhlut , Akhushtal, Akna , Akycha, Alaghom Naom Tzentel, Albino Spirit animals , Alektca , Alignak, Allanque , Allowat Sakima , Alom, Alowatsakima , Amaguq , Amala , Amimitl, Amitolane, Amotken , Andaokut , Andiciopec , Anerneq , Anetlacualtiliztli, Angalkuq , Angpetu Wi, Anguta, Angwusnasomtaka , Ani Hyuntikwalaski , Animal spirits , Aningan, Aniwye , Anog Ite , Anpao, Apanuugak , Apicilnic , Apikunni , Apotamkin , Apoyan Tachi , Apozanolotl, Apu Punchau, Aqalax , Arendiwane , Arnakua'gsak , Asdiwal , Asgaya Gigagei, Asiaq , Asin , Asintmah, Atacokai , Atahensic, Aticpac Calqui Cihuatl, Atira, Atisokan , Atius Tirawa , Atl, Atlacamani, Atlacoya, Atlatonin, Atlaua, Atshen , Auilix, Aulanerk , Aumanil , Aunggaak , Aunt Nancy , Awaeh Yegendji , Awakkule , Awitelin Tsta , Awonawilona, Ayauhteotl, Azeban, Baaxpee , Bacabs, Backlum Chaam, Bagucks , Bakbakwalanooksiwae , Balam, Baldhead , Basamacha , Basket Woman , Bead Spitter , Bear , Bear Medicine Woman , Bear Woman , Beaver , Beaver Doctor , Big Heads, Big Man Eater , Big Tail , Big Twisted Flute , Bikeh hozho, Bitol, Black Hactcin , Black Tamanous , Blind Boy , Blind Man , Blood Clot Boy , Bloody Hand , Blue-Jay , Bmola , Bolontiku, Breathmaker, Buffalo , Buluc Chabtan, Burnt Belly , Burnt Face , Butterfly , Cabaguil, Cacoch, Cajolom, Cakulha, Camaxtli, Camozotz, Cannibal Grandmother , Cannibal Woman , Canotila , Capa , Caprakan, Ca-the-ña, Cauac, Centeotl, Centzonuitznaua, Cetan , Chac Uayab Xoc, Chac, Chahnameed , Chakwaina Okya, Chalchihuitlicue, Chalchiuhtlatonal, Chalchiutotolin, Chalmecacihuilt, Chalmecatl, Chamer, Changing Bear Woman , Changing Woman , Chantico, Chaob, Charred Body , Chepi , Chibiabos ,Chibirias, Chiccan, Chicomecoatl, Chicomexochtli, Chiconahui, Chiconahuiehecatl, Chie, Child-Born-in-Jug , Chirakan, Chulyen , Cihuacoatl, Cin-an-ev , Cinteotl, Cipactli, Cirapé , Cit Chac Coh, Cit-Bolon-Tum, Citlalatonac, Citlalicue, Ciucoatl, Ciuteoteo, Cizin, Cliff ogre , Coatlicue, Cochimetl, Cocijo, Colel Cab, Colop U Uichkin, Copil, Coyolxauhqui, Coyopa, Coyote , Cripple Boy , Crow , Crow Woman , Cum hau, Cunawabi , Dagwanoenyent , Dahdahwat , Daldal , Deohako, Dhol , Diyin dine , Djien , Djigonasee , Dohkwibuhch , Dzalarhons , Dzalarhons, Eagentci , Eagle , Earth Shaman , Eeyeekalduk , Ehecatl, Ehlaumel , Eithinoha , Ekchuah, Enumclaw , Eototo, Esaugetuh Emissee , Esceheman, Eschetewuarha, Estanatlehi , Estasanatlehi , Estsanatlehi, Evaki, Evening Star, Ewah , Ewauna, Face , Faces of the Forests , False Faces , Famine , Fastachee , Fire Dogs , First Creator , First Man and First Woman, First Scolder , Flint Man , Flood , Flower Woman , Foot Stuck Child , Ga'an, Ga-gaah , Gahe, Galokwudzuwis , Gaoh, Gawaunduk, Geezhigo-Quae, Gendenwitha, Genetaska, Ghanan, Gitche Manitou, Glispa, Glooskap , Gluscabi , Gluskab , Gluskap, Godasiyo, Gohone , Great Seahouse, Greenmantle , Gucumatz, Gukumatz, Gunnodoyak, Gyhldeptis, Ha Wen Neyu , Hacauitz , Hacha'kyum, Hagondes , Hahgwehdiyu , Hamatsa , Hamedicu, Hanghepi Wi, Hantceiitehi , Haokah , Hastseoltoi, Hastshehogan , He'mask.as , Hen, Heyoka , Hiawatha , Hino, Hisakitaimisi, Hokhokw , Hotoru, Huehuecoyotl, Huehueteotl, Huitaca , Huitzilopochtli, Huixtocihuatl, Hummingbird, Hun hunahpu, Hun Pic Tok, Hunab Ku, Hunahpu Utiu, Hunahpu, Hunahpu-Gutch, Hunhau, Hurakan, Iatiku And Nautsiti, Ich-kanava , Ictinike , Idliragijenget , Idlirvirisong, Igaluk , Ignirtoq , Ikanam , Iktomi , Ilamatecuhtli, Illapa, Ilya p'a, i'noGo tied , Inti, Inua , Ioskeha , Ipalnemohuani, Isakakate, Ishigaq , Isitoq , Issitoq , Ite , Itzamná, Itzananohk`u, Itzlacoliuhque, Itzli, Itzpapalotl, Ix Chebel Yax, Ixbalanque, Ixchel, Ixchup, Ixmucane, Ixpiyacoc, Ixtab, Ixtlilton, Ixtubtin, Ixzaluoh, Iya , Iyatiku , Iztaccihuatl, Iztacmixcohuatl, Jaguar Night, Jaguar Quitze, Jogah , Kaakwha , Kabun , Kabun , Kachinas, Kadlu , Ka-Ha-Si , Ka-Ha-Si , Kaik , Kaiti , Kan, Kana'ti and Selu , Kanati, Kan-u-Uayeyab, Kan-xib-yui, Kapoonis , Katsinas, Keelut , Ketchimanetowa, Ketq Skwaye, Kianto, Kigatilik , Kilya, K'in, Kinich Ahau, Kinich Kakmo, Kishelemukong , Kisin, Kitcki Manitou, Kmukamch , Kokopelli , Ko'lok , Kukulcan, Kushapatshikan , Kutni , Kutya'I , Kwakwakalanooksiwae ,Kwatee , Kwekwaxa'we , Kwikumat , Kyoi , Lagua , Land Otter People , Lawalawa , Logobola , Loha, Lone Man , Long Nose , Loon , Loon Medicine , Loon Woman , Loo-wit, Macaw Woman, Macuilxochitl, Maho Peneta, Mahucutah, Makenaima , Malesk , Malina , Malinalxochi, Malsum, Malsumis , Mam, Mama Cocha, Man in moon , Manabozho , Manetuwak , Mani'to, Manitou , Mannegishi , Manu, Masaya, Masewi , Master of Life , Master Of Winds, Matshishkapeu , Mavutsinim , Mayahuel, Medeoulin , Mekala , Menahka, Meteinuwak , Metztli, Mexitl, Michabo, Mictecacihuatl, Mictlan, Mictlantecuhtli, Mikchich , Mikumwesu , Mitnal, Mixcoatl, Mongwi Kachinum , Morning Star, Motho and Mungo , Mulac, Muut , Muyingwa , Nacon, Nagenatzani, Nagi Tanka , Nagual, Nahual, Nakawé, Nanabojo, Nanabozho , Nanabush, Nanahuatzin, Nanautzin, Nanih Waiya, Nankil'slas , Nanook , Naum, Negafook , Nerrivik , Nesaru, Nianque , Nishanu , Nohochacyum, Nokomis, Nootaikok , North Star, Nujalik , Nukatem , Nunne Chaha , Ocasta, Ockabewis, Odzihozo , Ohtas , Oklatabashih, Old Man , Olelbis, Omacatl, Omecihuatl, Ometecuhtli, Onatha , One Tail of Clear Hair , Oonawieh Unggi , Opochtli, Oshadagea, Owl Woman , Pah , Pah, Paiowa, Pakrokitat , Pana , Patecatl, Pautiwa, Paynal, Pemtemweha , Piasa , Pikváhahirak , Pinga , Pomola , Pot-tilter , Prairie Falcon , Ptehehincalasanwin , Pukkeenegak , Qaholom, Qakma, Qiqirn , Quaoar , Quetzalcoatl, Qumu , Quootis-hooi, Rabbit, Ragno, Raven, Raw Gums , Rukko, Sagamores , Sagapgia , Sanopi , Saynday , Sedna, Selu, Shakuru, Sharkura, Shilup Chito Osh, Shrimp house, Sila , Sint Holo , Sio humis, Sisiutl , Skan , Snallygaster , Sosondowah , South Star, Spider Woman , Sta-au , Stonecoats , Sun, Sungrey , Ta Tanka , Tabaldak , Taime , Taiowa , Talocan, Tans , Taqwus , Tarhuhyiawahku, Tarquiup Inua , Tate , Tawa, Tawiscara, Ta'xet , Tcisaki , Tecciztecatl, Tekkeitserktock, Tekkeitsertok , Telmekic , Teoyaomqui, Tepeu, Tepeyollotl, Teteoinnan, Tezcatlipoca, Thobadestchin, Thoume', Thunder , Thunder Bird , Tieholtsodi, Tihtipihin , Tirawa , Tirawa Atius, Tlacolotl, Tlahuixcalpantecuhtli, Tlaloc, Tlaltecuhtli, Tlauixcalpantecuhtli, Tlazolteotl, Tohil, Tokpela ,Tonantzin , Tonatiuh, To'nenile, Tonenili , Tootega , Torngasak, Torngasoak , Trickster/Transformer , True jaguar, Tsentsa, Tsichtinako, Tsohanoai Tsonoqwa , Tsul 'Kalu , Tulugaak , Tumas , Tunkan ingan, Turquoise Boy , Twin Thunder Boys, Txamsem , Tzakol, Tzitzimime, Uazzale , Uchtsiti, Udó , Uentshukumishiteu , Ueuecoyotl, Ugly Way , Ugni , Uhepono , Uitzilopochtli, Ukat , Underwater Panthers , Unhcegila , Unipkaat , Unk, Unktomi , Untunktahe , Urcaguary, Utea , Uwashil , Vassagijik , Voltan, Wabosso , Wabun , Wachabe, Wah-Kah-Nee, Wakan , Wakanda , Wakan-Tanka, Wakinyan , Wan niomi , Wanagi , Wananikwe , Watavinewa , Water babies , Waukheon , We-gyet , Wemicus , Wendigo , Wentshukumishiteu , White Buffalo Woman, Whope , Wi , Wicahmunga , Wihmunga , Windigo, Winonah, Wisagatcak , Wisagatcak, Wishpoosh , Wiyot , Wovoka , Wuya , Xaman Ek, Xelas , Xibalba, Xilonen, Xipe Totec, Xiuhcoatl, Xiuhtecuhtli, Xiuhtecutli, Xmucane, Xochipili , Xochiquetzal, Xocotl, Xolotl, Xpiyacoc, Xpuch And Xtah, Yacatecuhtli, Yaluk, Yanauluha , Ya-o-gah , Yeba Ka, Yebaad, Yehl , Yeitso, Yiacatecuhtli, Yolkai Estsan, Yoskeha , Yum Kaax, Yuwipi , Zaramama, Zipaltonal, Zotz

Norse Deities, Giants and Monsters:

Aegir, Aesir, Alfrigg, Audumbla, Aurgelmir, Balder, Berchta, Bergelmir, Bor, Bragi, Brisings, Buri, Etin, Fenris, Forseti, Frey, Freyja, Frigga, Gefion, Gerda, Gode, Gymir, Harke, Heimdall, Hel, Hermod, Hodur, Holda, Holle, Honir, Hymir, Idun, Jormungandr, Ljolsalfs, Loki, Magni, Mimir, Mistarblindi, Muspel, Nanna, Nanni, Nerthus, Njord, Norns, Odin, Perchta, Ran, Rig, Segyn, Sif, Skadi, Skirnir, Skuld, Sleipnir, Surt, Svadilfari, tanngniotr, tanngrisnr, Thiassi, Thor, Thrud, Thrudgelmir, Thrym, Thurs, Tyr, Uller, Urd, Vali, Vali, Valkyries, Vanir, Ve, Verdandi, Vidar, Wode, Ymir

Pacific islands: Deities, Demigods and Immortal Monsters:

Abeguwo, Abere, Adaro, Afekan, Ai Tupua'i, 'Aiaru, Ala Muki, Alalahe, Alii Menehune, Aluluei, Aruaka, Asin, Atanea, Audjal, Aumakua, Babamik, Bakoa, Barong, Batara Kala, Buring Une, Darago, Dayang-Raca, De Ai, Dogai, Enda Semangko, Faumea, Giriputri, Goga, Haumea, Hiiaka', Hina, Hine, Hoa-Tapu, 'Imoa, Io, Kanaloa, Kanaloa, Kane, Kapo, Kava, Konori, Ku, Kuhuluhulumanu, Kuklikimoku, Kukoae, Ku'ula, Laka, Laulaati, Lono, Mahiuki, MakeMake, Marruni, Maru, Maui, Melu, Menehune, Moeuhane, MOO-LAU, Ndauthina, Ne Te-reere, Nevinbimbaau, Ngendei, Nobu, Oro, Ove, Paka'a, Papa, Pele, Quat, Rangi, Rati, Rati-mbati-ndua, Ratu-Mai-Mbula, Rua, Ruahatu, Saning Sri, Ta'aroa, Taaroa, Tamakaia, Tane, Tanemahuta, Tangaroa, Tawhaki, Tiki, Tinirau, Tu, Tuli, Turi-a-faumea, Uira, Ukupanipo, Ulupoka, Umboko Indra, Vanuatu, Wahini-Hal, Walutahanga, Wari-Ma-Te-Takere, Whaitiri, Whatu, Wigan

South American: Deities, Demigods, Beings of Divine Substance:

Abaangui, Aclla, Akewa, Asima Si, Atoja, Auchimalgen, Axomama, Bachué, Beru, Bochica, Boiuna, Calounger, Catequil, Cavillaca, Ceiuci, Chasca, Chie, Cocomama, Gaumansuri, Huitaca, Iae, Ilyap'a, Ina, Inti, Ituana, Jamaina , Jandira, Jarina, Jubbu-jang-sangne, Ka-ata-killa, Kilya, Kuat, Kun, Luandinha, Lupi, Mama Allpa, Mama Quilla, Mamacocha, Manco Capac, Maret-Jikky, Maretkhmakniam, Mariana, Oshossi, Pachamac, Pachamama, Perimbó, Rainha Barba, Si, Supai, Topétine, Viracocha, Yemanja (Imanje), Zume

Submitted May 28, 2023 at 04:42PM by dreamer100__ (From Reddit https://ift.tt/uTlQcN4)

Ji ji fu ji ji

a o e i i er ai ei ao ou an en ang eng ong i ia iao ie iu ian in iang ing iong u ua uo uai ui uan un uang ueng ü üe üan ün a o e er ai ao ou an en ang eng yi ya yao ye you yan yin yang ying yong wu wa wo wai wei wan wen wang weng yu yue yuan yun b ba bo bai bei bao ban ben bang beng bi biao bie bian bin bing bu p pa po pai pei pao pou pan pen pang peng pi piao pie pian pin ping pu m ma mo me mai mei mao mou man men mang meng mi miao mie miu mian min ming mu f fa fo fei fou fan fen fang feng fu d da de dai dei dao dou dan den dang deng dong di diao die diu dian ding du duo dui duan dun t ta te tai tei tao tou tan tang teng tong ti tiao tie tian ting tu tuo tui tuan tun n na ne nai nei nao nou nan nen nang neng nong ni niao nie niu nian nin niang ning nu nuo nuan nü nüe l la le lai lei lao lou lan lang leng long li lia liao lie liu lian lin liang ling lu luo luan lun lü lüe g ga ge gai gei gao gou gan gen gang geng gong gu gua guo guai gui guan gun guang k ka ke kai kei kao kou kan ken kang keng kong ku kua kuo kuai kui kuan kun kuang h ha he hai hei hao hou han hen hang heng hong hu hua huo huai hui huan hun huang z za ze zi zai zei zao zou zan zen zang zeng zong zu zuo zui zuan zun c ca ce ci cai cao cou can cen cang ceng cong cu cuo cui cuan cun s sa se si sai sao sou san sen sang seng song su suo sui suan sun zh zha zhe zhi zhai zhei zhao zhou zhan zhen zhang zheng zhong zhu zhua zhuo zhuai zhui zhuan zhun zhuang ch cha che chi chai chao chou chan chen chang cheng chong chu chua chuo chuai chui chuan chun chuang sh sha she shi shai shei shao shou shan shen shang sheng shu shua shuo shuai shui shuan shun shuang r re ri rao rou ran ren rang reng rong ru rua ruo rui ruan run j ji jia jiao jie jiu jian jin jiang jing jiong ju jue juan jun q qi qia qiao qie qiu qian qin qiang qing qiong qu que quan qun x xi xia xiao xie xiu xian xin xiang xing xiong xu xue xuan xun

Google at NeurIPS 2023

New Post has been published on https://thedigitalinsider.com/google-at-neurips-2023/

Google at NeurIPS 2023

This week the 37th annual Conference on Neural Information Processing Systems (NeurIPS 2023), the biggest machine learning conference of the year, kicks off in New Orleans, LA. Google is proud to be a Diamond Level sponsor of NeurIPS this year and will have a strong presence with >170 accepted papers, two keynote talks, and additional contributions to the broader research community through organizational support and involvement in >20 workshops and tutorials. Google is also proud to be a Platinum Sponsor for both the Women in Machine Learning and LatinX in AI workshops. We look forward to sharing some of our extensive ML research and expanding our partnership with the broader ML research community.

Attending for NeurIPS 2023 in person? Come visit the Google Research booth to learn more about the exciting work we’re doing to solve some of the field’s most interesting challenges. Visit the @GoogleAI X (Twitter) account to find out about Google booth activities (e.g., demos and Q&A sessions).

You can learn more about our latest cutting edge work being presented at the conference in the list below (Google affiliations highlighted in bold). And see Google DeepMind’s blog to learn more about their participation at NeurIPS 2023.

Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization Adel Javanmard, Vahab Mirrokni

Better Private Linear Regression Through Better Private Feature Selection Travis Dick, Jennifer Gillenwater*, Matthew Joseph

Binarized Neural Machine Translation Yichi Zhang, Ankush Garg, Yuan Cao, Łukasz Lew, Behrooz Ghorbani*, Zhiru Zhang, Orhan Firat

BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information Mehran Kazemi, Quan Yuan, Deepti Bhatia, Najoung Kim, Xin Xu, Vaiva Imbrasaite, Deepak Ramachandran

Boosting with Tempered Exponential Measures Richard Nock, Ehsan Amid, Manfred Warmuth

Concept Algebra for (Score-Based) Text-Controlled Generative Models Zihao Wang, Lin Gui, Jeffrey Negrea, Victor Veitch

Deep Contract Design via Discontinuous Networks Tonghan Wang, Paul Dütting, Dmitry Ivanov, Inbal Talgam-Cohen, David C. Parkes

Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection Cheng-Ju Ho, Chen-Hsuan Tai, Yen-Yu Lin, Ming-Hsuan Yang, Yi-Hsuan Tsai

Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew Walter

Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy Anastasia Koloskova*, Ryan McKenna, Zachary Charles, J Keith Rush, Hugh Brendan McMahan

Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products Tamas Sarlos, Xingyou Song, David P. Woodruff, Qiuyi (Richard) Zhang

Module-wise Adaptive Distillation for Multimodality Foundation Models

Chen Liang, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong, Tianyi Zhou

Multi-Swap k-Means++ Lorenzo Beretta, Vincent Cohen-Addad, Silvio Lattanzi, Nikos Parotsidis

OpenMask3D: Open-Vocabulary 3D Instance Segmentation Ayça Takmaz, Elisabetta Fedele, Robert Sumner, Marc Pollefeys, Federico Tombari, Francis Engelmann

Order Matters in the Presence of Dataset Imbalance for Multilingual Learning Dami Choi*, Derrick Xin, Hamid Dadkhahi, Justin Gilmer, Ankush Garg, Orhan Firat, Chih-Kuan Yeh, Andrew M. Dai, Behrooz Ghorbani

PopSign ASL v1.0: An Isolated American Sign Language Dataset Collected via Smartphones Thad Starner, Sean Forbes, Matthew So, David Martin, Rohit Sridhar, Gururaj Deshpande, Sam Sepah, Sahir Shahryar, Khushi Bhardwaj, Tyler Kwok, Daksh Sehgal, Saad Hassan, Bill Neubauer, Sofia Vempala, Alec Tan, Jocelyn Heath, Unnathi Kumar, Priyanka Mosur, Tavenner Hall, Rajandeep Singh, Christopher Cui, Glenn Cameron, Sohier Dane, Garrett Tanzer

Semi-Implicit Denoising Diffusion Models (SIDDMs) Yanwu Xu*, Mingming Gong, Shaoan Xie, Wei Wei, Matthias Grundmann, Kayhan Batmanghelich, Tingbo Hou

State2Explanation: Concept-Based Explanations to Benefit Agent Learning and User Understanding Devleena Das, Sonia Chernova, Been Kim

StoryBench: A Multifaceted Benchmark for Continuous Story Visualization Emanuele Bugliarello*, Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar, Han Zhang, Dumitru Erhan, Vittorio Ferrari, Pieter-Jan Kindermans, Paul Voigtlaender

Subject-driven Text-to-Image Generation via Apprenticeship Learning Wenhu Chen, Hexiang Hu, Yandong Li, Nataniel Ruiz, Xuhui Jia, Ming-Wei Chang, William W. Cohen

TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao*, Bahare Fatemi, Mike Burrows, Charith Mendis*, Bryan Perozzi

Training Chain-of-Thought via Latent-Variable Inference Du Phan, Matthew D. Hoffman, David Dohan*, Sholto Douglas, Tuan Anh Le, Aaron Parisi, Pavel Sountsov, Charles Sutton, Sharad Vikram, Rif A. Saurous

Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints Jayadev Acharya, Clement L. Canonne, Ziteng Sun, Himanshu Tyagi

What You See is What You Read? Improving Text-Image Alignment Evaluation Michal Yarom, Yonatan Bitton, Soravit Changpinyo, Roee Aharoni, Jonathan Herzig, Oran Lang, Eran Ofek, Idan Szpektor

When Does Confidence-Based Cascade Deferral Suffice? Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar

Accelerating Molecular Graph Neural Networks via Knowledge Distillation Filip Ekström Kelvinius, Dimitar Georgiev, Artur Petrov Toshev, Johannes Gasteiger

AVIS: Autonomous Visual Information Seeking with Large Language Model Agent Ziniu Hu*, Ahmet Iscen, Chen Sun, Kai-Wei Chang, Yizhou Sun, David Ross, Cordelia Schmid, Alireza Fathi

Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing “Spurious” Correlations Qingyao Sun, Kevin Patrick Murphy, Sayna Ebrahimi, Alexander D’Amour

Collaborative Score Distillation for Consistent Visual Editing Subin Kim, Kyungmin Lee, June Suk Choi, Jongheon Jeong, Kihyuk Sohn, Jinwoo Shin

CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graphs Guangyao Zhai, Evin Pınar Örnek, Shun-Cheng Wu, Yan Di, Federico Tombari, Nassir Navab, Benjamin Busam

Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy Amit Daniely, Nathan Srebro, Gal Vardi

A Computationally Efficient Sparsified Online Newton Method Fnu Devvrit*, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta, Cho-Jui Hsieh, Inderjit S Dhillon

DDF-HO: Hand-Held Object Reconstruction via Conditional Directed Distance Field Chenyangguang Zhang, Yan Di, Ruida Zhang, Guangyao Zhai, Fabian Manhardt, Federico Tombari, Xiangyang Ji

Double Auctions with Two-sided Bandit Feedback Soumya Basu, Abishek Sankararaman

Grammar Prompting for Domain-Specific Language Generation with Large Language Models Bailin Wang, Zi Wang, Xuezhi Wang, Yuan Cao, Rif A. Saurous, Yoon Kim

Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training Rie Johnson, Tong Zhang*

Large Graph Property Prediction via Graph Segment Training Kaidi Cao*, Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis*, Jure Leskovec, Bryan Perozzi

On Computing Pairwise Statistics with Local Differential Privacy Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon

On Student-teacher Deviations in Distillation: Does it Pay to Disobey? Vaishnavh Nagarajan, Aditya Krishna Menon, Srinadh Bhojanapalli, Hossein Mobahi, Sanjiv Kumar

Optimal Cross-learning for Contextual Bandits with Unknown Context Distributions Jon Schneider, Julian Zimmert

Near-Optimal k-Clustering in the Sliding Window Model David Woodruff, Peilin Zhong, Samson Zhou

Post Hoc Explanations of Language Models Can Improve Language Models Satyapriya Krishna, Jiaqi Ma, Dylan Z Slack, Asma Ghandeharioun, Sameer Singh, Himabindu Lakkaraju

Recommender Systems with Generative Retrieval Shashank Rajput*, Nikhil Mehta, Anima Singh, Raghunandan Hulikal Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Maheswaran Sathiamoorthy

Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh*, Kangwook Lee, Kimin Lee*

Replicable Clustering Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni, Grigoris Velegkas, Felix Zhou

Replicability in Reinforcement Learning Amin Karbasi, Grigoris Velegkas, Lin Yang, Felix Zhou

Riemannian Projection-free Online Learning Zihao Hu, Guanghui Wang, Jacob Abernethy

Sharpness-Aware Minimization Leads to Low-Rank Features Maksym Andriushchenko, Dara Bahri, Hossein Mobahi, Nicolas Flammarion

What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models Khashayar Gatmiry, Zhiyuan Li, Ching-Yao Chuang, Sashank Reddi, Tengyu Ma, Stefanie Jegelka

Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization Jui-Nan Yen, Sai Surya Duvvuri, Inderjit S Dhillon, Cho-Jui Hsieh

Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain

Boundary Guided Learning-Free Semantic Control with Diffusion Models Ye Zhu, Yu Wu, Zhiwei Deng, Olga Russakovsky, Yan Yan

Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference Tao Lei, Junwen Bai, Siddhartha Brahma, Joshua Ainslie, Kenton Lee, Yanqi Zhou, Nan Du*, Vincent Y. Zhao, Yuexin Wu, Bo Li, Yu Zhang, Ming-Wei Chang

Conformal Prediction for Time Series with Modern Hopfield Networks Andreas Auer, Martin Gauch, Daniel Klotz, Sepp Hochreiter

Does Visual Pretraining Help End-to-End Reasoning? Chen Sun, Calvin Luo, Xingyi Zhou, Anurag Arnab, Cordelia Schmid

Effective Robustness Against Natural Distribution Shifts for Models with Different Training Data Zhouxing Shi*, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel*, Yao Qin

Improving Neural Network Representations Using Human Similarity Judgments Lukas Muttenthaler*, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine Hermann, Andrew K. Lampinen, Simon Kornblith

Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala

Mnemosyne: Learning to Train Transformers with Transformers Deepali Jain, Krzysztof Choromanski, Avinava Dubey, Sumeet Singh, Vikas Sindhwani, Tingnan Zhang, Jie Tan

Nash Regret Guarantees for Linear Bandits Ayush Sawarni, Soumyabrata Pal, Siddharth Barman

A Near-Linear Time Algorithm for the Chamfer Distance Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten.

On Differentially Private Sampling from Gaussian and Product Distributions Badih Ghazi, Xiao Hu*, Ravi Kumar, Pasin Manurangsi

On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes Jia Lin Hau, Erick Delage, Mohammad Ghavamzadeh*, Marek Petrik

ResMem: Learn What You Can and Memorize the Rest Zitong Yang, Michal Lukasik, Vaishnavh Nagarajan, Zonglin Li, Ankit Singh Rawat, Manzil Zaheer, Aditya Krishna Menon, Sanjiv Kumar

Responsible AI (RAI) Games and Ensembles Yash Gupta, Runtian Zhai, Arun Suggala, Pradeep Ravikumar

RoboCLIP: One Demonstration Is Enough to Learn Robot Policies Sumedh A Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti

Robust Concept Erasure via Kernelized Rate-Distortion Maximization Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi

Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao

Simplicity Bias in 1-Hidden Layer Neural Networks Depen Morwani*, Jatin Batra, Prateek Jain, Praneeth Netrapalli

SLaM: Student-Label Mixing for Distillation with Unlabeled Examples Vasilis Kontonis, Fotis Iliopoulos, Khoa Trinh, Cenk Baykal, Gaurav Menghani, Erik Vee

SNAP: Self-Supervised Neural Maps for Visual Positioning and Semantic Understanding Paul-Edouard Sarlin*, Eduard Trulls, Marc Pollefeys, Jan Hosang, Simon Lynen

SOAR: Improved Indexing for Approximate Nearest Neighbor Search Philip Sun, David Simcha, Dave Dopson, Ruiqi Guo, Sanjiv Kumar

StyleDrop: Text-to-Image Synthesis of Any Style Kihyuk Sohn, Lu Jiang, Jarred Barber, Kimin Lee*, Nataniel Ruiz, Dilip Krishnan, Huiwen Chang*, Yuanzhen Li, Irfan Essa, Michael Rubinstein, Yuan Hao, Glenn Entis, Irina Blok, Daniel Castro Chin

Three Towers: Flexible Contrastive Learning with Pretrained Image Models Jannik Kossen*, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou

Two-Stage Learning to Defer with Multiple Experts Anqi Mao, Christopher Mohri, Mehryar Mohri, Yutao Zhong

AdANNS: A Framework for Adaptive Semantic Search Aniket Rege, Aditya Kusupati, Sharan Ranjit S, Alan Fan, Qingqing Cao, Sham Kakade, Prateek Jain, Ali Farhadi

Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer Bowen Tan*, Yun Zhu, Lijuan Liu, Eric Xing, Zhiting Hu, Jindong Chen

Causal-structure Driven Augmentations for Text OOD Generalization Amir Feder, Yoav Wald, Claudia Shi, Suchi Saria, David Blei

Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamas Sarlos, Adrian Weller

Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondence Grace Luo, Lisa Dunlap, Dong Huk Park, Aleksander Holynski, Trevor Darrell

Diffusion Self-Guidance for Controllable Image Generation Dave Epstein, Allan Jabri, Ben Poole, Alexei A Efros, Aleksander Holynski

Fully Dynamic k-Clustering in Õ(k) Update Time Sayan Bhattacharya, Martin Nicolas Costa, Silvio Lattanzi, Nikos Parotsidis

Improving CLIP Training with Language Rewrites Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian

<!–k-Means Clustering with Distance-Based Privacy Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong

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LayoutGPT: Compositional Visual Planning and Generation with Large Language Models Weixi Feng, Wanrong Zhu, Tsu-Jui Fu, Varun Jampani, Arjun Reddy Akula, Xuehai He, Sugato Basu, Xin Eric Wang, William Yang Wang

Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management Dhawal Gupta*, Yinlam Chow, Azamat Tulepbergenov, Mohammad Ghavamzadeh*, Craig Boutilier

Optimal Unbiased Randomizers for Regression with Label Differential Privacy Ashwinkumar Badanidiyuru, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Jacob Leeman, Pasin Manurangsi, Avinash V Varadarajan, Chiyuan Zhang

Paraphrasing Evades Detectors of AI-generated Text, but Retrieval Is an Effective Defense Kalpesh Krishna, Yixiao Song, Marzena Karpinska, John Wieting, Mohit Iyyer

ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation Shuyang Sun*, Weijun Wang, Qihang Yu*, Andrew Howard, Philip Torr, Liang-Chieh Chen*

Robust and Actively Secure Serverless Collaborative Learning Nicholas Franzese, Adam Dziedzic, Christopher A. Choquette-Choo, Mark R. Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang

SpecTr: Fast Speculative Decoding via Optimal Transport Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix Yu

Structured Prediction with Stronger Consistency Guarantees Anqi Mao, Mehryar Mohri, Yutao Zhong

Affinity-Aware Graph Networks Ameya Velingker, Ali Kemal Sinop, Ira Ktena, Petar Veličković, Sreenivas Gollapudi

ARTIC3D: Learning Robust Articulated 3D Shapes from Noisy Web Image Collections Chun-Han Yao*, Amit Raj, Wei-Chih Hung, Yuanzhen Li, Michael Rubinstein, Ming-Hsuan Yang, Varun Jampani

Black-Box Differential Privacy for Interactive ML Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer

Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits Haolin Liu, Chen-Yu Wei, Julian Zimmert

DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model

Xiuye Gu, Yin Cui*, Jonathan Huang, Abdullah Rashwan, Xuan Yang, Xingyi Zhou, Golnaz Ghiasi, Weicheng Kuo, Huizhong Chen, Liang-Chieh Chen*, David Ross

Easy Learning from Label Proportions Robert Busa-Fekete, Heejin Choi*, Travis Dick, Claudio Gentile, Andres Munoz Medina

Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks Eeshaan Jain, Tushar Nandy, Gaurav Aggarwal, Ashish Tendulkar, Rishabh Iyer, Abir De

Faster Differentially Private Convex Optimization via Second-Order Methods Arun Ganesh, Mahdi Haghifam*, Thomas Steinke, Abhradeep Guha Thakurta

Finding Safe Zones of Markov Decision Processes Policies Lee Cohen, Yishay Mansour, Michal Moshkovitz

Focused Transformer: Contrastive Training for Context Scaling Szymon Tworkowski, Konrad Staniszewski, Mikołaj Pacek, Yuhuai Wu*, Henryk Michalewski, Piotr Miłoś

Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu

H-Consistency Bounds: Characterization and Extensions Anqi Mao, Mehryar Mohri, Yutao Zhong

Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation David Brandfonbrener, Ofir Nachum, Joan Bruna

Most Neural Networks Are Almost Learnable Amit Daniely, Nathan Srebro, Gal Vardi

Multiclass Boosting: Simple and Intuitive Weak Learning Criteria Nataly Brukhim, Amit Daniely, Yishay Mansour, Shay Moran

NeRF Revisited: Fixing Quadrature Instability in Volume Rendering Mikaela Angelina Uy, Kiyohiro Nakayama, Guandao Yang, Rahul Krishna Thomas, Leonidas Guibas, Ke Li

Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation Wei-Ning Chen, Dan Song, Ayfer Ozgur, Peter Kairouz

Private Federated Frequency Estimation: Adapting to the Hardness of the Instance Jingfeng Wu*, Wennan Zhu, Peter Kairouz, Vladimir Braverman

RETVec: Resilient and Efficient Text Vectorizer Elie Bursztein, Marina Zhang, Owen Skipper Vallis, Xinyu Jia, Alexey Kurakin

Symbolic Discovery of Optimization Algorithms Xiangning Chen*, Chen Liang, Da Huang, Esteban Real, Kaiyuan Wang, Hieu Pham, Xuanyi Dong, Thang Luong, Cho-Jui Hsieh, Yifeng Lu, Quoc V. Le

A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence Junyi Zhang, Charles Herrmann, Junhwa Hur, Luisa F. Polania, Varun Jampani, Deqing Sun, Ming-Hsuan Yang

A Trichotomy for Transductive Online Learning Steve Hanneke, Shay Moran, Jonathan Shafer

A Unified Fast Gradient Clipping Framework for DP-SGD William Kong, Andres Munoz Medina

Unleashing the Power of Randomization in Auditing Differentially Private ML Krishna Pillutla, Galen Andrew, Peter Kairouz, H. Brendan McMahan, Alina Oprea, Sewoong Oh

(Amplified) Banded Matrix Factorization: A unified approach to private training Christopher A Choquette-Choo, Arun Ganesh, Ryan McKenna, H Brendan McMahan, Keith Rush, Abhradeep Guha Thakurta, Zheng Xu

Adversarial Resilience in Sequential Prediction via Abstention Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty

Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception Hassan Akbari, Dan Kondratyuk, Yin Cui, Rachel Hornung, Huisheng Wang, Hartwig Adam

Android in the Wild: A Large-Scale Dataset for Android Device Control Christopher Rawles, Alice Li, Daniel Rodriguez, Oriana Riva, Timothy Lillicrap

Benchmarking Robustness to Adversarial Image Obfuscations Florian Stimberg, Ayan Chakrabarti, Chun-Ta Lu, Hussein Hazimeh, Otilia Stretcu, Wei Qiao, Yintao Liu, Merve Kaya, Cyrus Rashtchian, Ariel Fuxman, Mehmet Tek, Sven Gowal

Building Socio-culturally Inclusive Stereotype Resources with Community Engagement Sunipa Dev, Jaya Goyal, Dinesh Tewari, Shachi Dave, Vinodkumar Prabhakaran

Consensus and Subjectivity of Skin Tone Annotation for ML Fairness Candice Schumann, Gbolahan O Olanubi, Auriel Wright, Ellis Monk Jr*, Courtney Heldreth, Susanna Ricco

Counting Distinct Elements Under Person-Level Differential Privacy Alexander Knop, Thomas Steinke

DICES Dataset: Diversity in Conversational AI Evaluation for Safety Lora Aroyo, Alex S. Taylor, Mark Diaz, Christopher M. Homan, Alicia Parrish, Greg Serapio-García, Vinodkumar Prabhakaran, Ding Wang

Does Progress on ImageNet Transfer to Real-world Datasets? Alex Fang, Simon Kornblith, Ludwig Schmidt

Estimating Generic 3D Room Structures from 2D Annotations Denys Rozumnyi*, Stefan Popov, Kevis-kokitsi Maninis, Matthias Nießner, Vittorio Ferrari

Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias Yue Yu, Yuchen Zhuang, Jieyu Zhang, Yu Meng, Alexander Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang

MADLAD-400: A Multilingual And Document-Level Large Audited Dataset Sneha Kudugunta, Isaac Caswell, Biao Zhang, Xavier Garcia, Derrick Xin, Aditya Kusupati, Romi Stella, Ankur Bapna, Orhan Firat

Mechanic: A Learning Rate Tuner Ashok Cutkosky, Aaron Defazio, Harsh Mehta

NAVI: Category-Agnostic Image Collections with High-Quality 3D Shape and Pose Annotations Varun Jampani, Kevis-kokitsi Maninis, Andreas Engelhardt, Arjun Karpur, Karen Truong, Kyle Sargent, Stefan Popov, Andre Araujo, Ricardo Martin Brualla, Kaushal Patel, Daniel Vlasic, Vittorio Ferrari, Ameesh Makadia, Ce Liu*, Yuanzhen Li, Howard Zhou

Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations Anudhyan Boral, Zhong Yi Wan, Leonardo Zepeda-Nunez, James Lottes, Qing Wang, Yi-Fan Chen, John Roberts Anderson, Fei Sha

Restart Sampling for Improving Generative Processes Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, Tommi Jaakkola

Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial? Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu, Qifan Wang, Hongning Wang, Haifeng Xu

Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union Zifu Wang, Maxim Berman, Amal Rannen-Triki, Philip Torr, Devis Tuia, Tinne Tuytelaars, Luc Van Gool, Jiaqian Yu, Matthew B. Blaschko

RoboHive: A Unified Framework for Robot Learning Vikash Kumar, Rutav Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Abhishek Gupta, Aravind Rajeswaran

SatBird: Bird Species Distribution Modeling with Remote Sensing and Citizen Science Data Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi, Hugo Larochelle, David Rolnick

Sparsity-Preserving Differentially Private Training of Large Embedding Models Badih Ghazi, Yangsibo Huang*, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners Yonglong Tian, Lijie Fan, Phillip Isola, Huiwen Chang, Dilip Krishnan

Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning Zachary Charles, Nicole Mitchell, Krishna Pillutla, Michael Reneer, Zachary Garrett

Universality and Limitations of Prompt Tuning Yihan Wang, Jatin Chauhan, Wei Wang, Cho-Jui Hsieh

Unsupervised Semantic Correspondence Using Stable Diffusion Eric Hedlin, Gopal Sharma, Shweta Mahajan, Hossam Isack, Abhishek Kar, Andrea Tagliasacchi, Kwang Moo Yi

YouTube-ASL: A Large-Scale, Open-Domain American Sign Language-English Parallel Corpus Dave Uthus, Garrett Tanzer, Manfred Georg

The Noise Level in Linear Regression with Dependent Data Ingvar Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni

Movie Review | The Iron Dragon Strikes Back (Kuei, 1979)

If you approach Bruceploitation with an eye for taxonomy, The Iron Dragon Strikes Back, also known as The Gold Connection, falls into the non-wacky, trying to be a good movie part of the genre. And more specifically, it falls into the deeply cynical part of the genre. This is a story about a group of friends who foolishly steal some gold stashed by smugglers and end up paying for it dearly as they’re ruthlessly hunted down. Lots of people end up dead. This is not one of those upbeat, goofy Bruceploitation movies by any stretch. Based on the premise, The Gold Connection is obviously the more accurate title, but it’s also kinda lame. The Iron Dragon Strikes Back is much less true to the spirit of the movie, but it also sounds way cooler, and allows for some Star Wars knockoff title graphics. I’m pretty sure this is what John Ford meant by print the legend.

This is directed by Kuei Chih-Hung, best known for his psychedelic vomitorium The Boxer’s Omen. (One of my favourite moviegoing experiences was getting to see this on the big screen during a Shaw Brothers retrospective. I don’t personally partake in the wacky tobacky, but I would wager this would be a good movie to partake during, and there was a distinct aroma around the entrance of the theatre.) I’ve also seen from him Hex, the supernatural (or is it) spookfest, and Killer Constable, the ultra-mean, ultra-cynical kung fu flick starring Chen Kuan-Tai, and this feels spiritually in line with the latter. Kuei made this on the cheap outside of the Shaw Brothers studio system (the production company on this is “Goldig Films”, which is a lot funnier of you’ve seen their Golden Harvest ripoff logo and heard their Shaw Brothers ripoff fanfare music), and like the work of Larry Cohen, that guerilla style gives it a certain jittery energy.

The bulk of the movie is set in the places the Hong Kong tourism board doesn’t want you to see, the camera squeezing into the slums and back alleys, and even the modernist surfaces of a shopping mall reveals to be hiding a great deal of disrepair and neglect. This energy seeps into the action as well, a constant series of bruising fight scenes where characters are stumbling over barrels, furniture and other detritus and where every hit looks extra painful. (One especially wince-inducing moment has a character dragged across a gravel pit as their arm is stuck in the door of a bus.) And it feeds the mounting sense of paranoia, as the low level thugs who antagonize the heroes early on are replaced by a covert killer who strikes them down one by one when they least expect. Other Hong Kong movies have evoked the feeling of being eaten alive by the city, but it feels especially potent here. (As to who the killer is, if you’ve seen enough Hong Kong action movies you’ll spot him right away, but I would still discourage you from reading the cast list too closely.) There isn’t much levity here, aside from an early scene where a character pans Roger Vadim’s When a Woman is in Love: “No fighting. Real boring.”

This stars Bruce Li, the most respectful of the Bruce Lee imitators, whose serious-minded approach may not provide enough spice to save weaker efforts, but works great when he has the movie to back him up. He actually doesn’t even attempt to mimic the real Lee here outside of sporting an Adidas tracksuit in one scene (this comes during a studio film shoot that descends into bloody chaos, which may or may not be a jab by either the star or the director at their usual employers). Aside from this, he gets to have a non-Lee inspired wardrobe, and I must note that I thought a few of his looks (red turtleneck with side-zip boots, bomber jacket with bellbottom jeans) were pretty cool, although that might be my menswear-blog-poisoned brain talking. I’ll also note that after having watched so many Bruceploitation movies on subpar transfers, it was great to see this on an attractive Blu-ray from Gold Ninja Video. It’s not a restoration, but the odd scratch on the print nicely complemented the texture of the movie, and the richness of the dark colours accentuated the downbeat tone.

If the movie suffers, it’s that it divides our attention between Li and his friends, so that none of them really feel like complete characters and earn our emotional investment. You can compare this to the attention with which Soul Brothers of Kung Fu builds the relationship between Bruce Li and Carl Scott, so that when things go south, it stings all the more, while here I felt like I was watching bad things happen to people I didn’t really know. But this does end on a strong note, with a weapon-filled confrontation in a dark, cramped apartment where Li surprises the villain with the flash of his camera. It worked great against the dick-vag monster in The Strangeness, and it works great here.

阿弥陀佛. Universe started together when your xin (mind) is shakened. Yi than zhin too many 32,000. Xing fu yuan man. It is created even before any time and space. Alaya consciousness is created. How big? Bigger than the universe, it is zhe xin. Lun wui is to tai yim and change it. Meng sarm kin seng (sarm leng) where u have chap seng (dirty, tham chan chi, ko sarng wud too use to it this turned into wisdom, chi seng sickness). Sarng meng is sarng wud. Zhuan seng to become zhi wai. Fui fuk zhi seng, seng fat (cheng fo). Close to Enlightenment which with no differentiation. Mona become pin deng. Xin fo peng deng. That is the state of Buddhahood. Time & space came from one source. Me but still got fa sheng. Western Pureland is created by it too of Amitabha Buddha but it does not have 'zhi xin dong nian'. Non differentiation mind. The truth behind the tooth. The papaya croach story. When you let go of yourself, you got the world. When you let go of this world, you will get Western Pureland. Tree is life. Today is world environmental day, Jun 5th 2022. A tree is a universe. Money is printed from destroying a universe (tree) and then used in ways to cause more harm to the planet, the universe. Change it dont chase for it, seek and manage. Everything you do, everyone you see, dharma help you see the truth all attachments become saha world, then suffering arise, everything is Amituofo, the way you see the world becomes Amituofo. Ching jing peng deng sure reborn in Pureland. Practicex3. Zhen fa meng ru lai (Kuan yin aeons ago. Kuan ser yin ru lai teaches Kuan Ser Yin pusa the disciple, er kern zhui ling). My true nature is the Buddha. Wui guai zhi sing. Dharma is the cure sickness (Fart). Li ( bu shen bu miet) ser jen, xiang sher jia. Xin is chen, ser is jia. True or false also dont be too attached. Bu ji xing dong nien jiu ser the tips. With a sickness, ji, xing, dong, nien, fern, bie, zhe, zhuo (6 gen). Karn po. Yi cher yau wei fart, sern miet fa. Mei lai mei chu, sam mo se de mei you. Wo you 3 bao. Ching jing peng den. Arhat avhieve zeng jue. Pusa practice Peng deng xin to achieve chen deng zeng jue, Buddha chen wu sarng chen deng jue. Ser jie wan wu ser yi ti. This body is my manifestation. Dont do anything in saha world that makes you attached too much that you couldnt let go and seek rebirth in Western Pureland. Wu xin is Amituofo. Amituofo is my xin. Every ben xin is Amituofo. You seek yourself. Let yourself be found, not search outside but inside. The world is using a piece of paper to weigh everything, cert for qualification, paper owns land and houses. A piece of paper becomes everything, your self worth as light as a piece of paper....Jing zhen guo. Fang xia chai but ku, let go and burden's gone...Compassion is your focus, is your life. If no compassion then only left unhappiness and sorrow. Happiness in Saha world is the start of unhappiness. Go back to the neutral state is happiness, no unhappiness. You need to peace down, silent give rise to wisdom. My heart is my way place. Wo xin ju shi tao chang. Fo got 52 jie ti. Let go, become Arhat, let go become Pusa and let go become Buddha.

Chaotu prayers / retreat: Lunch by 1.30 pm on Pusa 8 kwan zhai day. Note: June 21st in china kills dog, Korea, Vietnam, use zhi lig, fa lig, fo lig. Then, it will combined at a great strength to change the world. 30 days be vegan. House concept, a house is like a cell. No matter how beautiful, you are trapped within. Your body is already like a house. Ur problem is u let go of ur house and came here, that is the dna effect of leaving Chn to Msia living a house there like grandpa.

Part 1

Nian fo - 8x108 x 2 (6 syllable), 16x108 x 6 (4 syllable) Done 28

Kuan yin - 8x108 x 2, 100% Done 28

Ksitigarbha 8x108 x 2, 100% Done 28

Heart sutra, Done 67

Tadyatha om gate gate paragate parasamgate bodhi svaha x 108 Done 5.5

Surangama mantra - 4×108, 100% Done 5.5

Stupa mantra, Done 69

A va la ka kia 108, Done 5.75

Compassionate mantra, Done 66

Namo he lai dan na tuo lai ye ye, namo o li ye, po lo je ti se pe la ye, pu ti sa tuo po ye, mo he sa tuo po ye, mo he jia lu ni jia ye, Dan zhe tan.

Om Du lin, Du lin, Jia Du lin, Soha. Done x 5.75

Part 2

Long Medicine Buddha mantra, Medicine Buddha heart mantra 108, Done 3.75

Om mani padme hum, a a sa sa maha - 8x108 Done 18

Usnisa Vijaya mantra, Om Bhrum Soha - 8x108 x 2, Done 18

Om Ah Hum 8x108 x 2, Done 19

Manjushri mantra 4x108, 100% Done 3.5

Om Avira Hum Kachara Mum Soha Done x 3.25

Earth store mantra 4x108, 100% Done 3.5

7th Past Parents mantra 4x108, 100% Done 3.5

Long life mantra 4x108, 100% Done 3.5

Om Maiyura Krante Svaha Done x 3.5

Namo Bo bo Ti li, Cher (li) To li, Dan tuo ye tuo ye, Done 3.25

Om ye ye nan 4x108, Done 7.25

Food mantra 4x108, Done 13.5

Water offering mantra, Done 3.25

Liberate small water being mantra, Done 3.75

Part 3

Sakyamuni Buddha mantra 4x108 Done 3.25

Tara mantras

- Green 4x108, Done 3.25

- White 4x108, Done 3

Om Tare Tuttare Ture Mama Ayuh Punya Jñana (Gyana) Pustim (Pusting) Kuru Svaha

- Red 4x108, 100% Done 3

Setrap mantra 4x108, Done 3.25

Om Benza Wiki Bitana Soha 4x108, Done 2.5

~ Shanti Siddhi Hom 4x108, Done 2.5

Eliminate karma by 7 buddhas mantra 4x108, Done 3

Pudong Ru Lai Zhou

Pureland rebirth mantra 4x108, Done 4.25

Light mantra 4x108, Done 4.25

Om Benza Sato Hung 4×108, Done 33.25

Mantra multiplier mantra 4x108, Done 41.5

Others:

Om tore tore cha tore so poho

Om Lan Soha

Om Chrine

Om Brim

Om Pu Kam (Pureland).

Am Bi Chanaga.

Om da de da de mohe dade svaha.

Om Mani Padme Hung A a sa sa maha

Namo bhagavate...x4

Om Amida Ayu Dadi Soha

Food Mantra

Ganlu sui zhou

Namo bo bo ti li, cher (li) to li, dan tuo ye tuo ye

Om mani facili hum

You need to nian fo then can achieve fo

But now, you only nian 6 realm of rebirth how to achieve fo?

You are fo why cannot become fo?

Becos u never let go of the 6 realm or rebirth activities. Greed, anger, ignorance (3 poisons need to let go 1st)

All ppl are the creation of their minds.

Then can u nian fo (real valuable activities the rests are useless)? All problems are due to cant let go of afflictions. Zhe xin give rise to Amituofo & Western Pureland. All existence is creation of the mind. How to let go of everything and seek rebirth in Pureland. All existence, this Saha world is creation of the mind / messy thoughts. Our body is our own manifestation of the (our) mind. Let go of the thoughts and mind, it will take u to next creation / manifestation. Practice but forget don't put practice into the mind. Be forgetful but only remember where you are going, Western Pureland so keep that in mind. This is called freedom of the mind (like depicted in Heart Sutra, freedom - zezai), our only aim which is zezai warng serng si fang ji le sher chieh. Love is the opposite of wisdom. Wisdom can only arise from compassion if you can turn love to compassion. Love can be a distraction to a cultivator. Love is not real. Reason stuck in 6 realms of retribution is love (because got form and conditions), everything of this nature is impermanent, hence love is not real, jia xiang. U cant come out. Dont let jia siang chi pien ni de xin. Dont be fooled by a false image / appearance. Use peng deng xin to console sentient beings, Buddha treat everyone like his father, the King. The thanxiang, cow agarwood no longer here. Go Western Pureland: (Haitao Fashi) Use 3 fu tien, kan ern de fu tien, zhun jing de fu tien, cher pei de fu tien. (Chin Kung Fashi) 3 fu, xiao shun fu mu / respective teachers - 1. Filial piety is the root. 2. Take refuges, san kwai yi / chi kai. 3. Sam sun yan ko (first, nian fo yin, cheng fo zhi ko). Ying guang fa shi. Wu liang yik zhi zhai fan now, Da zhi zai tien wang tha men di fu de guang ming bu nen kan dao. In front of rulai, it's gone. Fan fu. We have 51 mental factors

https:///wiki/Mental_factors_(Buddhism)

- sing so 11 san de (seong ying), fanuo de 26 (seong ying). The 10 recitation method x 9 times in a day, 2 minutes each time, nian nian bu warng Amituofo. The tipper is must be continuous....then u see improvement (kungfu). Must use chen xing. (Learn from the best learn from the Muslims. Let go to do prayer when the time comes.) Ying ye, 5 jie 10 sarn. Huan xi pu ser. Pu ser, cai yuen guenx2 lai. All existence are manifestation of karma, the fruits of causes (combination of effects). All are swihuan de. At one point, u are here, there, everywhere in the universe of existence, different space and time like a multiverse. This body is like a bowl of water with lots of salt added (a.k.a. sufferings which r the effects of ur past karma). Everything u have contact with is to let u 'suffer' all circumstances created in some past lives that u cant see or remember. The purpose of cultivation is to realised this truth (6 realms of rebirth). To break and escape this cycle is to achieve Buddhahood. Fastest way is to see all existences as one and of the same. If u destroy ur own defilements u are doing the same for others only when u have compassion and use 'peng deng, chi pei, po re xin'. This body is yeap bo. Life is like a bowl of salt water. Living it is like drinking it. You need to add more water not morr salt so it geys better over time. Get out of it, pour it back to the sea. You dont need to drink it. It is where water would return (thru true self discovery and enlightenment, practice of Buddhism to the highest level).

4 Universal Vows

Also sometimes called the Bodhisattva Vows, as they are essential to the Bodhisattva path of Mahāyāna Buddhism.

1. Sentient beings are limitless; I vow to liberate them.

眾生無邊誓願度

Zhòngshēng wúbiān shìyuàn dù

Zhong Shen Wu Bian Ser Yuan Tu

2. Afflictions are endless; I vow to eradicate them.

煩惱無盡誓願斷

Fánnǎo wújìn shìyuàn duàn

Fan Now Wu Jing Ser Yuan Tuan.

3. Teachings are infinite; I vow to learn them.

法門無量誓願學

Fǎmén wúliàng shìyuàn xué

Fa Men Wu Liang Ser Yuan Shue.

4. Buddhahood is supreme; I vow to attain it.

佛道無上誓願成

Fú dào wú shàng shìyuàn chéng

Fo Dao Wu Sharng Ser Yuan Chern.

Say this 4 things, ask to let go:

Ken ching qiu fangxia yuen:

1. Du bu qu. Sorry.

2. Ching yuan liang wo. Please forgive me.

3. Xie xie ni. Thank you.

4. Wo ai ni. I love you.

Duration of cultivation:

41 years. May 3rd, 2022 - May 3rd, 2062 (add one year worth of cultivation)

When the Prince, Siddhartha Gautama bids farewell to his father saying:

Even my love for Yasodhara…and my son…

cannot remove the pain I feel.

For I know that they too will have to suffer,

grow old…and die.

Like you, like me, like us all.

Yes. We must all die…

and be reborn…

and die again,

and be reborn and die,

and be reborn and die again.

No man can ever escape that curse.

Then that…is my task. I…will lift that curse.

At the moment of the attainment of awakening, the Buddha uttered the following:

"I travelled through the rounds of countless births through the cycle of existence,

Seeking but not finding the builder of this house [of 'self'] and again and again, I faced the suffering of new birth.

O Housebuilder, you have now been seen,

You shall not build a house again for me.

Your beams [defilements] have now been broken, Your ridgepole [ignorance] utterly shattered.

My mind has attained the supreme

'nibbana' ('blowing out')

Realised is the unconditioned, Achieved is the end of craving."

- Siddhartha Gautama

(Dhammapada Verses 153 and 154)

When attachment arises in our mind it does not feel harmful; on the contrary it usually feels beneficial. Therefore, it is important to contemplate repeatedly the faults of attachment and to recognize it as a delusion whose only function is to cause us harm.

Remember one cannot trust what you sees because ur eyes are imperfecg and cannot see the absolute truth. This organ limitation is bounded by it creations. It is created from delusion. What is deluded cannot revealed it undeluded nature. Just like the blind leading the blind...it is still within the same state which is called suffering. When u see without seeing and when u have sight of not using any organ is when the truth would be revealed and the absolute truth is the state overcoming delusion or samsara, the true escape of realm of rebirths. Is when u crossed the other shore. The state of relization, Buddhood, the enlightment.

Chen Kuan Tai’s tiger style on the set of “Executioners from Shaolin”

If you haven’t gotten the Shawscope Vol. 1, 12-film, 8-Disc box set from Arrow Video, it is a must have! It’s incredible.

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Chen Kuan-Tai in The Boxer from Shantung / 馬永貞 (1972)