Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning

28 June 2020

Papers citing "Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning"

10 / 10 papers shown

Title
HG2P: Hippocampus-inspired High-reward Graph and Model-Free Q-Gradient Penalty for Path Planning and Motion Control Haoran Wang Yaoru Sun Zeshen Tang Haibo Shi Chenyuan Jiao 21 0 0 12 Oct 2024
Policy Contrastive Imitation Learning Jialei Huang Zhao-Heng Yin Yingdong Hu Yang Gao 17 3 0 06 Jul 2023
Smooth Imitation Learning via Smooth Costs and Smooth Policies Sapana Chaudhary Balaraman Ravindran 19 1 0 03 Nov 2021
A Pragmatic Look at Deep Imitation Learning Kai Arulkumaran D. Lillrank 16 9 0 04 Aug 2021
Visual Adversarial Imitation Learning using Variational Models Rafael Rafailov Tianhe Yu Aravind Rajeswaran Chelsea Finn SSL 28 49 0 16 Jul 2021
What Matters for Adversarial Imitation Learning? Manu Orsini Anton Raichuk Léonard Hussenot Damien Vincent Robert Dadashi Sertan Girgin M. Geist Olivier Bachem Olivier Pietquin Marcin Andrychowicz 39 77 0 01 Jun 2021
Measuring the Algorithmic Efficiency of Neural Networks Danny Hernandez Tom B. Brown 226 94 0 08 May 2020
A Closer Look at Accuracy vs. Robustness Yao-Yuan Yang Cyrus Rashtchian Hongyang R. Zhang Ruslan Salakhutdinov Kamalika Chaudhuri OOD 66 26 0 05 Mar 2020
Weighted Linear Bandits for Non-Stationary Environments Yoan Russac Claire Vernade Olivier Cappé 82 101 0 19 Sep 2019
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 273 2,888 0 15 Sep 2016