Yu, Lantao

19 publications

WACV 2025 A Data Perspective on Enhanced Identity Preservation for Diffusion Personalization Xingzhe He, Zhiwen Cao, Nick Kolkin, Lantao Yu, Kun Wan, Helge Rhodin, Ratheesh Kalarot

CVPR 2024 DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-Based 3D Vision Lu Ling, Yichen Sheng, Zhi Tu, Wentian Zhao, Cheng Xin, Kun Wan, Lantao Yu, Qianyu Guo, Zixun Yu, Yawen Lu, Xuanmao Li, Xingpeng Sun, Rohan Ashok, Aniruddha Mukherjee, Hao Kang, Xiangrui Kong, Gang Hua, Tianyi Zhang, Bedrich Benes, Aniket Bera

AAAI 2023 Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching Lantao Yu, Tianhe Yu, Jiaming Song, Willie Neiswanger, Stefano Ermon

ICML 2022 A General Recipe for Likelihood-Free Bayesian Optimization Jiaming Song, Lantao Yu, Willie Neiswanger, Stefano Ermon

NeurIPS 2022 Generalizing Bayesian Optimization with Decision-Theoretic Entropies Willie Neiswanger, Lantao Yu, Shengjia Zhao, Chenlin Meng, Stefano Ermon

ICLR 2022 GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang

ECML-PKDD 2021 Multi-Agent Imitation Learning with Copulas Hongwei Wang, Lantao Yu, Zhangjie Cao, Stefano Ermon

NeurIPS 2021 Pseudo-Spherical Contrastive Divergence Lantao Yu, Jiaming Song, Yang Song, Stefano Ermon

NeurIPS 2020 Autoregressive Score Matching Chenlin Meng, Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon

AISTATS 2020 Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation Yuxuan Song, Ning Miao, Hao Zhou, Lantao Yu, Mingxuan Wang, Lei Li

AAAI 2020 Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip Yuxuan Song, Minkai Xu, Lantao Yu, Hao Zhou, Shuo Shao, Yong Yu

NeurIPS 2020 MOPO: Model-Based Offline Policy Optimization Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Y Zou, Sergey Levine, Chelsea Finn, Tengyu Ma

ICML 2020 Training Deep Energy-Based Models with F-Divergence Minimization Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon

ICML 2019 CoT: Cooperative Training for Generative Modeling of Discrete Data Sidi Lu, Lantao Yu, Siyuan Feng, Yaoming Zhu, Weinan Zhang

AAAI 2019 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

ICML 2019 Lipschitz Generative Adversarial Nets Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Yong Yu, Zhihua Zhang

NeurIPS 2019 Meta-Inverse Reinforcement Learning with Probabilistic Context Variables Lantao Yu, Tianhe Yu, Chelsea Finn, Stefano Ermon

ICML 2019 Multi-Agent Adversarial Inverse Reinforcement Learning Lantao Yu, Jiaming Song, Stefano Ermon

AAAI 2017 SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient Lantao Yu, Weinan Zhang, Jun Wang, Yong Yu