AltschulerWu-Lab/MuLANN
Code and data of the "Multi-domain adversarial learning" paper, Schoenauer-Sebag et al., accepted at ICLR 2019
LuaGPL-3.0
Stargazers
- AccioF. Hoffmann-La Roche AG, Switzerland
- ameroyerKyutai Labs
- aschoenauer-sebag
- Beat0n
- BinhuiXieBeijing Institute of Technology
- chrisyxueUESTC
- daiszh
- dhx000Peking University
- e96031413National Yang Ming Chiao Tung University
- fly51flyPRIS
- GeoffNNParis
- h-jiaMelbourne
- Haofan144UC Santa Cruz
- he0x
- hucanpeiHUST
- iCGY96Peking University
- jofferyUniversity of Delaware
- junyoonQureator, Inc
- MaximilianWinterMunich
- MikhailovichGlushkov
- moskomuleRIKEN AIP
- otakbekuLemaries
- pjt123China，Chongqing
- Polaris231uestc
- sabyasachisMila and Université Laval
- santiagolopezgSan Francisco, CA
- silver-1347
- xwjabc
- yhy1117ByteDance
- yotofu
- yuanzhigang10Tsinghua; Alibaba
- Zhi-Feng-ZhangBeijing University of Posts and Telecommunications
- zhoudiNEUNortheastern university
- zimo-k
- zpyovo