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elay Zhao
1。奖励在测试时间扩散模型中的奖励引入了迭代改进，适用于蛋白质和DNA设计Masatoshi uehara，Xingyu SU，Yulai Zhao，Yulai Zhao，Xiner LI，Aviv Regev，Shuiwang Ji，Sergey Ji，Sergey Levine，Sergey Levine，Tommaso Biancalani Arxiv Arxiv Preprint 2。与奖励指导一代的扩散模型中的推理时间对齐：教程和评论Masatoshi uehara，Yulai Zhao，Chenyu Wang，Xiner LI，Aviv Regev，Sergey Legev，Sergey Legev，Tommaso Biancalani Arxiv Arxiv Arxiv Preprint 3。Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding Xiner Li, Yulai Zhao , Chenyu Wang, Gabriele Scalia, Gokcen Eraslan, Surag Nair, Tommaso Biancalani, Shuiwang Ji, Aviv Regev, Sergey Levine, Masatoshi Uehara arXiv preprint 4.理解基于扩散模型的基于增强学习的微调：教程和评论Masatoshi uehara *，Yulai Zhao *，Tommaso Biancalani，Sergey Levine Arxiv Preprint 5。连续时间扩散模型的微调作为熵调查的对照果片uehara *，Yulai Zhao *，Kevin Black，Kevin Black，Ehsan Hajiramezanali，Gabriele Scalia，Nathaniel Lee Diemant，Alex M Tseng，Alex M Tseng，Tommaso Biancalani，Sergey/Sergey Levine在弱凸度假设下优化表现风险Yulai Zhao Neurips 2022关于机器学习优化的研讨会
Shenglong Xu：课程vitae
[ 5 ] Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, YuQing Xie, Xiang Fu, Alex Strasser, Shenglong Xu , Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik Bekkers, Michael Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon，PietroLiò，Rose Yu，StephanGünnemann，Jure Leskovec，Heng JI，Jimeng Sun，Regina Barzilay，Tommi Jaakkola，Connor W. Coley，Coley，Coley，Xiaoning Qian，Xiaofeng Qian，Xiaofeng Qian，Tess Smidt和Shuiiwang Ji。“量子，原子和连续体系中科学的人工智能”。Arxiv预印型ARXIV：2307。08423（2023）。