Lantao Yu | DeepAI

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Sergey Levine
379 publications
Jun Wang
360 publications
Lei Li
255 publications
Stefano Ermon
168 publications
Chelsea Finn
167 publications
Weinan Zhang
146 publications
Hao Zhou
145 publications
James Zou
123 publications
Yong Yu
102 publications
Tengyu Ma
97 publications
Yi Wu
77 publications

∙ 12/07/2021

A Unified Framework for Multi-distribution Density Ratio Estimation

Binary density ratio estimation (DRE), the problem of estimating the rat...

11 Lantao Yu, et al. ∙

∙ 07/31/2021

Manifold-Inspired Single Image Interpolation

Manifold models consider natural-image patches to be on a low-dimensiona...

0 Lantao Yu, et al. ∙

∙ 07/10/2021

Multi-Agent Imitation Learning with Copulas

Multi-agent imitation learning aims to train multiple agents to perform ...

7 Hongwei Wang, et al. ∙

∙ 03/17/2021

Fast and High-Quality Blind Multi-Spectral Image Pansharpening

Blind pansharpening addresses the problem of generating a high spatial-r...

1 Lantao Yu, et al. ∙

∙ 01/20/2021

Quarter Laplacian Filter for Edge Aware Image Processing

This paper presents a quarter Laplacian filter that can preserve corners...

21 Yuanhao Gong, et al. ∙

∙ 01/20/2021

A Discrete Scheme for Computing Image's Weighted Gaussian Curvature

Weighted Gaussian Curvature is an important measurement for images. Howe...

4 Yuanhao Gong, et al. ∙

∙ 10/01/2020

Understanding Self-supervised Learning with Dual Deep Networks

We propose a novel theoretical framework to understand self-supervised l...

52 Yuandong Tian, et al. ∙

∙ 07/12/2020

Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation

Auto-regressive sequence generative models trained by Maximum Likelihood...

4 Yuxuan Song, et al. ∙

∙ 05/27/2020

MOPO: Model-based Offline Policy Optimization

Offline reinforcement learning (RL) refers to the problem of learning po...

15 Tianhe Yu, et al. ∙

∙ 04/03/2020

Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip

Although Shannon theory states that it is asymptotically optimal to sepa...

0 Yuxuan Song, et al. ∙

∙ 03/06/2020

Training Deep Energy-Based Models with f-Divergence Minimization

Deep energy-based models (EBMs) are very flexible in distribution parame...

14 Lantao Yu, et al. ∙

∙ 11/21/2019

Improving Unsupervised Domain Adaptation with Variational Information Bottleneck

Domain adaptation aims to leverage the supervision signal of source doma...

0 Yuxuan Song, et al. ∙

∙ 09/20/2019

Meta-Inverse Reinforcement Learning with Probabilistic Context Variables

Providing a suitable reward function to reinforcement learning can be di...

6 Lantao Yu, et al. ∙

∙ 07/30/2019

Multi-Agent Adversarial Inverse Reinforcement Learning

Reinforcement learning agents are prone to undesired behaviors due to re...

8 Lantao Yu, et al. ∙

∙ 02/15/2019

Lipschitz Generative Adversarial Nets

In this paper we study the convergence of generative adversarial network...

0 Zhiming Zhou, et al. ∙

∙ 11/06/2018

Deep Reinforcement Learning for Green Security Games with Real-Time Information

Green Security Games (GSGs) have been proposed and applied to optimize p...

0 Yufei Wang, et al. ∙

∙ 07/02/2018

Understanding the Effectiveness of Lipschitz Constraint in Training of GANs via Gradient Analysis

This paper aims to bring a new perspective for understanding GANs, by de...

4 Zhiming Zhou, et al. ∙

∙ 05/14/2018

Exploiting Data and Human Knowledge for Predicting Wildlife Poaching

Poaching continues to be a significant threat to the conservation of wil...

0 Swaminathan Gurumurthy, et al. ∙

∙ 04/11/2018

CoT: Cooperative Training for Generative Modeling

We propose Cooperative Training (CoT) for training generative models tha...

0 Sidi Lu, et al. ∙

∙ 09/13/2017

A Study of AI Population Dynamics with Million-agent Reinforcement Learning

We conduct an empirical study on discovering the ordered collective dyna...

0 Yaodong Yang, et al. ∙

∙ 09/13/2017

An Empirical Study of AI Population Dynamics with Million-agent Reinforcement Learning

In this paper, we conduct an empirical study on discovering the ordered ...

0 Yaodong Yang, et al. ∙

∙ 09/18/2016

SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient

As a new way of training generative models, Generative Adversarial Nets ...

0 Lantao Yu, et al. ∙

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