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2020 – today
- 2024
[c32]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:
DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-based 3D Vision. CVPR 2024: 22160-22169- [c31]Zichuan Liu, Ke Wang, Mingyuan Wu, Lantao Yu, Klara Nahrstedt, Xin Lu:
I-Matting: Improved Trimap-Free Image Matting. ICME 2024: 1-6 - [i31]Yuanhao Gong, Lantao Yu, Guanghui Yue:
Isotropic Gaussian Splatting for Real-Time Radiance Field Rendering. CoRR abs/2403.14244 (2024) - 2023
- [c30]Lantao Yu, Tianhe Yu, Jiaming Song, Willie Neiswanger, Stefano Ermon:
Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching. AAAI 2023: 11016-11024 - [i30]Lantao Yu, Tianhe Yu, Jiaming Song, Willie Neiswanger, Stefano Ermon:
Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching. CoRR abs/2303.02569 (2023) - [i29]Xingzhe He, Zhiwen Cao, Nicholas Kolkin, Lantao Yu, Helge Rhodin, Ratheesh Kalarot:
A Data Perspective on Enhanced Identity Preservation for Diffusion Personalization. CoRR abs/2311.04315 (2023) - [i28]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:
DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-based 3D Vision. CoRR abs/2312.16256 (2023) - 2022
- [j2]Lantao Yu
, Dehong Liu, Hassan Mansour, Petros T. Boufounos:
Fast and High-Quality Blind Multi-Spectral Image Pansharpening. IEEE Trans. Geosci. Remote. Sens. 60: 1-17 (2022) - [c29]Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang:
GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation. ICLR 2022 - [c28]Jiaming Song, Lantao Yu, Willie Neiswanger, Stefano Ermon:
A General Recipe for Likelihood-free Bayesian Optimization. ICML 2022: 20384-20404 - [c27]Willie Neiswanger, Lantao Yu, Shengjia Zhao, Chenlin Meng, Stefano Ermon:
Generalizing Bayesian Optimization with Decision-theoretic Entropies. NeurIPS 2022 - [i27]Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang:
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation. CoRR abs/2203.02923 (2022) - [i26]Jiaming Song, Lantao Yu, Willie Neiswanger, Stefano Ermon:
A General Recipe for Likelihood-free Bayesian Optimization. CoRR abs/2206.13035 (2022) - [i25]Willie Neiswanger, Lantao Yu, Shengjia Zhao, Chenlin Meng, Stefano Ermon:
Generalizing Bayesian Optimization with Decision-theoretic Entropies. CoRR abs/2210.01383 (2022) - 2021
- [j1]Jiankai Sun, Lantao Yu, Pinqian Dong, Bo Lu, Bolei Zhou:
Adversarial Inverse Reinforcement Learning With Self-Attention Dynamics Model. IEEE Robotics Autom. Lett. 6(2): 1880-1886 (2021) - [c26]Yuanhao Gong, Wenming Tang, Lebin Zhou, Lantao Yu, Guoping Qiu:
A Discrete Scheme for Computing Image's Weighted Gaussian Curvature. ICIP 2021: 1919-1923 - [c25]Yuanhao Gong, Wenming Tang, Lebin Zhou, Lantao Yu, Guoping Qiu:
Quarter Laplacian Filter For Edge Aware Image Processing. ICIP 2021: 1959-1963 - [c24]Lantao Yu, Jiaming Song, Yang Song, Stefano Ermon:
Pseudo-Spherical Contrastive Divergence. NeurIPS 2021: 22348-22362 - [c23]Hongwei Wang, Lantao Yu, Zhangjie Cao, Stefano Ermon:
Multi-agent Imitation Learning with Copulas. ECML/PKDD (1) 2021: 139-156 - [i24]Yuanhao Gong, Wenming Tang, Lebin Zhou, Lantao Yu, Guoping Qiu:
A Discrete Scheme for Computing Image's Weighted Gaussian Curvature. CoRR abs/2101.07927 (2021) - [i23]Yuanhao Gong, Wenming Tang, Lebin Zhou, Lantao Yu, Guoping Qiu:
Quarter Laplacian Filter for Edge Aware Image Processing. CoRR abs/2101.07933 (2021) - [i22]Lantao Yu, Dehong Liu, Hassan Mansour, Petros T. Boufounos:
Fast and High-Quality Blind Multi-Spectral Image Pansharpening. CoRR abs/2103.09943 (2021) - [i21]Hongwei Wang, Lantao Yu, Zhangjie Cao, Stefano Ermon:
Multi-Agent Imitation Learning with Copulas. CoRR abs/2107.04750 (2021) - [i20]Lantao Yu, Kuida Liu, Michael T. Orchard:
Manifold-Inspired Single Image Interpolation. CoRR abs/2108.00145 (2021) - [i19]Lantao Yu, Jiaming Song, Yang Song, Stefano Ermon:
Pseudo-Spherical Contrastive Divergence. CoRR abs/2111.00780 (2021) - [i18]Lantao Yu, Yujia Jin, Stefano Ermon:
A Unified Framework for Multi-distribution Density Ratio Estimation. CoRR abs/2112.03440 (2021) - 2020
- [c22]Yuxuan Song, Minkai Xu, Lantao Yu, Hao Zhou, Shuo Shao, Yong Yu:
Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip. AAAI 2020: 5834-5841 - [c21]Yuxuan Song, Ning Miao, Hao Zhou, Lantao Yu, Mingxuan Wang, Lei Li:
Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation. AISTATS 2020: 122-132 - [c20]Yuxuan Song, Lantao Yu, Zhangjie Cao, Zhiming Zhou, Jian Shen, Shuo Shao, Weinan Zhang, Yong Yu:
Improving Unsupervised Domain Adaptation with Variational Information Bottleneck. ECAI 2020: 1499-1506 - [c19]Lantao Yu, Dehong Liu, Hassan Mansour, Petros T. Boufounos, Yanting Ma:
Blind Multi-Spectral Image Pan-Sharpening. ICASSP 2020: 1429-1433 - [c18]Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon:
Training Deep Energy-Based Models with f-Divergence Minimization. ICML 2020: 10957-10967 - [c17]Chenlin Meng, Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon:
Autoregressive Score Matching. NeurIPS 2020 - [c16]Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Y. Zou, Sergey Levine, Chelsea Finn, Tengyu Ma:
MOPO: Model-based Offline Policy Optimization. NeurIPS 2020 - [i17]Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon:
Training Deep Energy-Based Models with f-Divergence Minimization. CoRR abs/2003.03463 (2020) - [i16]Yuxuan Song, Minkai Xu, Lantao Yu, Hao Zhou, Shuo Shao, Yong Yu:
Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip. CoRR abs/2004.01454 (2020) - [i15]Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma:
MOPO: Model-based Offline Policy Optimization. CoRR abs/2005.13239 (2020) - [i14]Yuxuan Song, Ning Miao, Hao Zhou, Lantao Yu, Mingxuan Wang, Lei Li:
Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation. CoRR abs/2007.06018 (2020) - [i13]Yuandong Tian, Lantao Yu, Xinlei Chen, Surya Ganguli:
Understanding Self-supervised Learning with Dual Deep Networks. CoRR abs/2010.00578 (2020) - [i12]Chenlin Meng, Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon:
Autoregressive Score Matching. CoRR abs/2010.12810 (2020)
2010 – 2019
- 2019
- [c15]Yufei Wang, Zheyuan Ryan Shi, Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang:
Deep Reinforcement Learning for Green Security Games with Real-Time Information. AAAI 2019: 1401-1408 - [c14]Lantao Yu, Michael T. Orchard:
Single Image Interpolation Exploiting Semi-local Similarity. ICASSP 2019: 1722-1726 - [c13]Lantao Yu, Michael T. Orchard:
When Spatially-Variant Filtering Meets Low-Rank Regularization: Exploiting Non-Local Similarity for Single Image Interpolation. ICIP 2019: 200-204 - [c12]Lantao Yu, Michael T. Orchard:
Accurate Edge Location Identification Based on Location-Directed Image Modeling. ICIP 2019: 2971-2975 - [c11]Sidi Lu, Lantao Yu, Siyuan Feng, Yaoming Zhu, Weinan Zhang:
CoT: Cooperative Training for Generative Modeling of Discrete Data. ICML 2019: 4164-4172 - [c10]Lantao Yu, Jiaming Song, Stefano Ermon:
Multi-Agent Adversarial Inverse Reinforcement Learning. ICML 2019: 7194-7201 - [c9]Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Yong Yu, Zhihua Zhang:
Lipschitz Generative Adversarial Nets. ICML 2019: 7584-7593 - [c8]Lantao Yu, Tianhe Yu, Chelsea Finn, Stefano Ermon:
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables. NeurIPS 2019: 11749-11760 - [i11]Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Yong Yu, Zhihua Zhang:
Lipschitz Generative Adversarial Nets. CoRR abs/1902.05687 (2019) - [i10]Lantao Yu, Jiaming Song, Stefano Ermon:
Multi-Agent Adversarial Inverse Reinforcement Learning. CoRR abs/1907.13220 (2019) - [i9]Lantao Yu, Tianhe Yu, Chelsea Finn, Stefano Ermon:
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables. CoRR abs/1909.09314 (2019) - [i8]Yuxuan Song, Lantao Yu, Zhangjie Cao, Zhiming Zhou, Jian Shen, Shuo Shao, Weinan Zhang, Yong Yu:
Improving Unsupervised Domain Adaptation with Variational Information Bottleneck. CoRR abs/1911.09310 (2019) - 2018
- [c7]Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang:
Deep Reinforcement Learning for Green Security Game with Online Information. AAAI Workshops 2018: 325-333 - [c6]Yaodong Yang, Lantao Yu, Yiwei Bai, Ying Wen, Weinan Zhang, Jun Wang:
A Study of AI Population Dynamics with Million-agent Reinforcement Learning. AAMAS 2018: 2133-2135 - [c5]Swaminathan Gurumurthy, Lantao Yu, Chenyan Zhang, Yongchao Jin, Weiping Li, Xiaodong Zhang, Fei Fang:
Exploiting Data and Human Knowledge for Predicting Wildlife Poaching. COMPASS 2018: 29:1-29:8 - [c4]Lantao Yu, Michael T. Orchard:
Location-Directed Image Modeling and its Application to Image Interpolation. ICIP 2018: 2192-2196 - [i7]Sidi Lu, Lantao Yu, Weinan Zhang, Yong Yu:
CoT: Cooperative Training for Generative Modeling. CoRR abs/1804.03782 (2018) - [i6]Swaminathan Gurumurthy, Lantao Yu, Chenyan Zhang, Yongchao Jin, Weiping Li, Haidong Zhang, Fei Fang:
Exploiting Data and Human Knowledge for Predicting Wildlife Poaching. CoRR abs/1805.05356 (2018) - [i5]Zhiming Zhou, Yuxuan Song, Lantao Yu, Yong Yu:
Understanding the Effectiveness of Lipschitz Constraint in Training of GANs via Gradient Analysis. CoRR abs/1807.00751 (2018) - [i4]Yufei Wang, Zheyuan Ryan Shi, Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang:
Deep Reinforcement Learning for Green Security Games with Real-Time Information. CoRR abs/1811.02483 (2018) - 2017
- [c3]Lantao Yu, Weinan Zhang, Jun Wang, Yong Yu:
SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient. AAAI 2017: 2852-2858 - [c2]Xuejian Wang, Lantao Yu, Kan Ren, Guanyu Tao, Weinan Zhang, Yong Yu, Jun Wang:
Dynamic Attention Deep Model for Article Recommendation by Learning Human Editors' Demonstration. KDD 2017: 2051-2059 - [c1]Jun Wang, Lantao Yu, Weinan Zhang, Yu Gong, Yinghui Xu, Benyou Wang, Peng Zhang, Dell Zhang:
IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models. SIGIR 2017: 515-524 - [i3]Jun Wang, Lantao Yu, Weinan Zhang, Yu Gong, Yinghui Xu, Benyou Wang, Peng Zhang, Dell Zhang:
IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models. CoRR abs/1705.10513 (2017) - [i2]Yaodong Yang, Lantao Yu, Yiwei Bai, Jun Wang, Weinan Zhang, Ying Wen, Yong Yu:
An Empirical Study of AI Population Dynamics with Million-agent Reinforcement Learning. CoRR abs/1709.04511 (2017) - 2016
- [i1]Lantao Yu, Weinan Zhang, Jun Wang, Yong Yu:
SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient. CoRR abs/1609.05473 (2016)
Coauthor Index
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