SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient. - Lantao Yu; Weinan Zhang 001; Jun Wang 012; Yong Yu 001 (AAAI, 2017)

Dynamic Attention Deep Model for Article Recommendation by Learning Human Editors' Demonstration. - Xuejian Wang; Lantao Yu; Kan Ren; Guanyu Tao; Weinan Zhang 001; Yong Yu 001; Jun Wang 012 (KDD, 2017)

IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models. - Jun Wang 012; Lantao Yu; Weinan Zhang 001; Yu Gong; Yinghui Xu; Benyou Wang; Peng Zhang 002; Dell Zhang (SIGIR, 2017)

An Empirical Study of AI Population Dynamics with Million-agent Reinforcement Learning. - Yaodong Yang 001; Lantao Yu; Yiwei Bai; Jun Wang 012; Weinan Zhang 001; Ying Wen 001; Yong Yu 001 (CoRR, 2017)

Deep Reinforcement Learning for Green Security Game with Online Information. - Lantao Yu; Yi Wu 013; Rohit Singh; Lucas Joppa; Fei Fang 001 (AAAI Workshops, 2018)

A Study of AI Population Dynamics with Million-agent Reinforcement Learning. - Yaodong Yang 001; Lantao Yu; Yiwei Bai; Ying Wen 001; Weinan Zhang 001; Jun Wang 012 (AAMAS, 2018)

Exploiting Data and Human Knowledge for Predicting Wildlife Poaching. - Swaminathan Gurumurthy; Lantao Yu; Chenyan Zhang; Yongchao Jin; Weiping Li; Xiaodong Zhang; Fei Fang 001 (COMPASS, 2018)

Location-Directed Image Modeling and its Application to Image Interpolation. - Lantao Yu; Michael T. Orchard (ICIP, 2018)

CoT: Cooperative Training for Generative Modeling. - Sidi Lu; Lantao Yu; Weinan Zhang 001; Yong Yu 001 (CoRR, 2018)

Exploiting Data and Human Knowledge for Predicting Wildlife Poaching. - Swaminathan Gurumurthy; Lantao Yu; Chenyan Zhang; Yongchao Jin; Weiping Li; Haidong Zhang; Fei Fang 001 (CoRR, 2018)

Understanding the Effectiveness of Lipschitz Constraint in Training of GANs via Gradient Analysis. - Zhiming Zhou 001; Yuxuan Song; Lantao Yu; Yong Yu 001 (CoRR, 2018)

Deep Reinforcement Learning for Green Security Games with Real-Time Information. - Yufei Wang; Zheyuan Ryan Shi; Lantao Yu; Yi Wu 013; Rohit Singh; Lucas Joppa; Fei Fang 001 (AAAI, 2019)

Single Image Interpolation Exploiting Semi-local Similarity. - Lantao Yu; Michael T. Orchard (ICASSP, 2019)

When Spatially-Variant Filtering Meets Low-Rank Regularization: Exploiting Non-Local Similarity for Single Image Interpolation. - Lantao Yu; Michael T. Orchard (ICIP, 2019)

Accurate Edge Location Identification Based on Location-Directed Image Modeling. - Lantao Yu; Michael T. Orchard (ICIP, 2019)

CoT: Cooperative Training for Generative Modeling of Discrete Data. - Sidi Lu; Lantao Yu; Siyuan Feng; Yaoming Zhu; Weinan Zhang 001 (ICML, 2019)

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

Lipschitz Generative Adversarial Nets. - Zhiming Zhou 001; Jiadong Liang; Yuxuan Song; Lantao Yu; Hongwei Wang 004; Weinan Zhang 001; Yong Yu 001; Zhihua Zhang 004 (ICML, 2019)

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

Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip. - Yuxuan Song; Minkai Xu; Lantao Yu; Hao Zhou 012; Shuo Shao 001; Yong Yu 001 (AAAI, 2020)

Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation. - Yuxuan Song; Ning Miao; Hao Zhou 012; Lantao Yu; Mingxuan Wang; Lei Li 005 (AISTATS, 2020)

Improving Unsupervised Domain Adaptation with Variational Information Bottleneck. - Yuxuan Song; Lantao Yu; Zhangjie Cao; Zhiming Zhou 001; Jian Shen 003; Shuo Shao 001; Weinan Zhang 001; Yong Yu 001 (ECAI, 2020)

Blind Multi-Spectral Image Pan-Sharpening. - Lantao Yu; Dehong Liu; Hassan Mansour; Petros T. Boufounos; Yanting Ma (ICASSP, 2020)

Training Deep Energy-Based Models with f-Divergence Minimization. - Lantao Yu; Yang Song 011; Jiaming Song; Stefano Ermon (ICML, 2020)

Autoregressive Score Matching. - Chenlin Meng; Lantao Yu; Yang Song 011; Jiaming Song; Stefano Ermon (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 001 (NeurIPS, 2020)

Understanding Self-supervised Learning with Dual Deep Networks. - Yuandong Tian; Lantao Yu; Xinlei Chen; Surya Ganguli (CoRR, 2020)

A Discrete Scheme for Computing Image's Weighted Gaussian Curvature. - Yuanhao Gong; Wenming Tang; Lebin Zhou; Lantao Yu; Guoping Qiu (ICIP, 2021)

Quarter Laplacian Filter For Edge Aware Image Processing. - Yuanhao Gong; Wenming Tang; Lebin Zhou; Lantao Yu; Guoping Qiu (ICIP, 2021)

Pseudo-Spherical Contrastive Divergence. - Lantao Yu; Jiaming Song; Yang Song 011; Stefano Ermon (NeurIPS, 2021)

Multi-agent Imitation Learning with Copulas. - Hongwei Wang 004; Lantao Yu; Zhangjie Cao; Stefano Ermon (ECML/PKDD (1), 2021)

Manifold-Inspired Single Image Interpolation. - Lantao Yu; Kuida Liu; Michael T. Orchard (CoRR, 2021)

A Unified Framework for Multi-distribution Density Ratio Estimation. - Lantao Yu; Yujia Jin; Stefano Ermon (CoRR, 2021)

Adversarial Inverse Reinforcement Learning With Self-Attention Dynamics Model. - Jiankai Sun; Lantao Yu; Pinqian Dong; Bo Lu 001; Bolei Zhou (IEEE Robotics Autom. Lett., 2021)

GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation. - Minkai Xu; Lantao Yu; Yang Song 011; Chence Shi; Stefano Ermon; Jian Tang 005 (ICLR, 2022)

A General Recipe for Likelihood-free Bayesian Optimization. - Jiaming Song; Lantao Yu; Willie Neiswanger; Stefano Ermon (ICML, 2022)

Generalizing Bayesian Optimization with Decision-theoretic Entropies. - Willie Neiswanger; Lantao Yu; Shengjia Zhao; Chenlin Meng; Stefano Ermon (NeurIPS, 2022)

Fast and High-Quality Blind Multi-Spectral Image Pansharpening. - Lantao Yu; Dehong Liu; Hassan Mansour; Petros T. Boufounos (IEEE Trans. Geosci. Remote. Sens., 2022)

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

A Data Perspective on Enhanced Identity Preservation for Diffusion Personalization. - Xingzhe He; Zhiwen Cao; Nicholas I. Kolkin; Lantao Yu; Helge Rhodin; Ratheesh Kalarot (CoRR, 2023)

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 001; Lantao Yu; Qianyu Guo; Zixun Yu; Yawen Lu; Xuanmao Li; Xingpeng Sun; et al. (CVPR, 2024)

I-Matting: Improved Trimap-Free Image Matting. - Zichuan Liu; Ke Wang; Mingyuan Wu; Lantao Yu; Klara Nahrstedt; Xin Lu (ICME, 2024)

Isotropic Gaussian Splatting for Real-Time Radiance Field Rendering. - Yuanhao Gong; Lantao Yu; Guanghui Yue 001 (CoRR, 2024)

Prompt-Guided Mask Proposal for Two-Stage Open-Vocabulary Segmentation. - Yu-Jhe Li; Xinyang Zhang; Kun Wan 001; Lantao Yu; Ajinkya Kale; Xin Lu (CoRR, 2024)

A Filter for Minimizing Gaussian Curvature on 3D Triangular Meshes. - Yuanhao Gong; Tan Tang; Zeyu Yang; Lantao Yu (ISBI, 2025)

A Data Perspective on Enhanced Identity Preservation for Diffusion Personalization. - Xingzhe He; Zhiwen Cao; Nicholas I. Kolkin; Lantao Yu; Kun Wan 001; Helge Rhodin; Ratheesh Kalarot (WACV, 2025)

Ultra-Malin: Robotic Ultrasound Mapping and Localization via Implicit Neural Representation. - Shuai Zhang; Bo Ouyang; Cancan Zhao; Lantao Yu; Leiqi Tian; Tongyu Jia; Zhijun Xing; Kawal S. Rhode (IEEE Trans. Instrum. Meas., 2025)