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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
portfolio
publications
SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
Lantao Yu, Weinan Zhang, Jun Wang, and Yong Yu. The 31st AAAI conference on Artificial Intelligence. AAAI 2017.
IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models
Jun Wang, Lantao Yu, Weinan Zhang, Yu Gong, Yinghui Xu, Benyou Wang, Peng Zhang and Dell Zhang. The 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. SIGIR 2017. Best Paper Award Honorable Mention
A Dynamic Attention Deep Model for Article Recommendation by Learning Human Editors’ Demonstration
Xuejian Wang*, Lantao Yu* (equal contribution), Kan Ren, Guanyu Tao, Weinan Zhang, Yong Yu, Jun Wang. The 23rd SIGKDD Conference on Knowledge Discovery and Data Mining. KDD 2017.
A Study of AI Population Dynamics with Million-agent Reinforcement Learning
Yaodong Yang*, Lantao Yu*, Yiwei Bai* (equal contribution), Jun Wang, Weinan Zhang, Ying Wen, Yong Yu. The 17th International Conference on Autonomous Agents and Multi-Agent Systems. AAMAS 2018.
Deep Reinforcement Learning for Green Security Game with Online Information
Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa and Fei Fang. AAAI-18 Artificial Intelligence for Imperfect-Information Games Workshop.
CoT: Cooperative Training for Generative Modeling of Discrete Data
Sidi Lu, Lantao Yu, Siyuan Feng, Yaoming Zhu, Weinan Zhang, Yong Yu. The 36th International Conference on Machine Learning. ICML 2019.
Multi-Agent Adversarial Inverse Reinforcement Learning
Lantao Yu, Jiaming Song, Stefano Ermon. The 36th International Conference on Machine Learning. ICML 2019. (Long Oral)
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables
Lantao Yu*, Tianhe Yu* (equal contribution), Chelsea Finn, Stefano Ermon. The 33rd Conference on Neural Information Processing Systems. NeurIPS 2019.
Adversarial Inverse Reinforcement Learning with Self-attention Dynamics Model
Jiankai Sun, Lantao Yu, Pinqian Dong, Bo Lu, Bolei Zhou. IEEE Robotics and Automation Letters. RA-L 2021 and ICRA 2021.
Exploiting Real-World Data and Human Knowledge for Predicting Wildlife Poaching
Swaminathan Gurumurthy, Lantao Yu, Chenyan Zhang, Yongchao Jin, Weiping Li, Xiaodong Zhang, Fei Fang. ACM SIGCAS Conference on Computing and Sustainable Societies. COMPASS 2018.
Understanding the Effectiveness of Lipschitz-Continuity in Generative Adversarial Nets
Zhiming Zhou, Yuxuan Song, Lantao Yu, Hongwei Wang, Zhihua Zhang, Weinan Zhang, Yong Yu. Preprint. arXiv:1807.00751
Deep Reinforcement Learning for Green Security Games with Real-Time Information
Yufei Wang, Zheyuan Ryan Shi, Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang. The Thirty-Third AAAI Conference on Artificial Intelligence. AAAI 2019.
Lipschitz Generative Adversarial Nets
Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Yong Yu, Zhihua Zhang. The 36th International Conference on Machine Learning. ICML 2019.
Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip
Yuxuan Song, Minkai Xu, Lantao Yu, Hao Zhou, Shuo Shao, Yong Yu. AAAI 2020.
Variational Bottleneck Domain Adaptation
Yuxuan Song, Lantao Yu, Zhangjie Cao, Zhiming Zhou, Jian Shen, Shuo Shao, Weinan Zhang, Yong Yu. ECAI 2020.
Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation
Yuxuan Song, Ning Miao, Hao Zhou, Lantao Yu, Mingxuan Wang, Lei Li. AISTATS 2020.
Training Deep Energy-Based Models with f-Divergence Minimization
Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon. The 37th International Conference on Machine Learning. ICML 2020.
MOPO: Model-based Offline Policy Optimization
Tianhe Yu*, Garrett Thomas* (equal contribution), Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma. The 34th Conference on Neural Information Processing Systems. NeurIPS 2020.
Autoregressive Score Matching
Chenlin Meng, Lantao Yu, Yang Song, Jiaming Song, and Stefano Ermon. The 34th Conference on Neural Information Processing Systems. NeurIPS 2020.
Understanding Self-supervised Learning with Dual Deep Networks
Yuandong Tian, Lantao Yu, Xinlei Chen, Surya Ganguli. Preprint. arXiv:2010.00578
Multi-Agent Imitation Learning with Copulas
Hongwei Wang*, Lantao Yu* (equal contribution), Zhangjie Cao, Stefano Ermon. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML-PKDD 2021.
Pseudo-Spherical Contrastive Divergence
Lantao Yu, Jiaming Song, Yang Song, Stefano Ermon. The 35th Conference on Neural Information Processing Systems. NeurIPS 2021.
A Unified Framework for Multi-distribution Density Ratio Estimation
Lantao Yu, Yujia Jin, Stefano Ermon. Preprint. arXiv:2112.03440
GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation
Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang. The Tenth International Conference on Learning Representations. ICLR 2022. (Oral Presentation)
A General Recipe for Likelihood-free Bayesian Optimization
Jiaming Song*, Lantao Yu* (equal contribution), Willie Neiswanger, Stefano Ermon. The 39th International Conference on Machine Learning. ICML 2022. (Long Oral, Top 2.2%)