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Learning Domain Invariant Representations in Goal-conditioned Block MDPs

Learning Domain Invariant Representations in Goal-conditioned Block MDPs

27 October 2021
Beining Han
Chongyi Zheng
Harris Chan
Keiran Paster
Michael Ruogu Zhang
Jimmy Ba
    OOD
    AI4CE
ArXivPDFHTML

Papers citing "Learning Domain Invariant Representations in Goal-conditioned Block MDPs"

42 / 42 papers shown
Title
Entity-based Reinforcement Learning for Autonomous Cyber Defence
Entity-based Reinforcement Learning for Autonomous Cyber Defence
Isaac Symes Thompson
Alberto Caron
Chris Hicks
V. Mavroudis
AAML
78
3
0
23 Oct 2024
How to Solve Contextual Goal-Oriented Problems with Offline Datasets?
How to Solve Contextual Goal-Oriented Problems with Offline Datasets?
Ying Fan
Jingling Li
Adith Swaminathan
Aditya Modi
Ching-An Cheng
OffRL
83
0
0
14 Aug 2024
Domain Adversarial Neural Networks for Domain Generalization: When It
  Works and How to Improve
Domain Adversarial Neural Networks for Domain Generalization: When It Works and How to Improve
Anthony Sicilia
Xingchen Zhao
Seong Jae Hwang
OOD
AI4CE
19
75
0
07 Feb 2021
Contrastive Behavioral Similarity Embeddings for Generalization in
  Reinforcement Learning
Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning
Rishabh Agarwal
Marlos C. Machado
Pablo Samuel Castro
Marc G. Bellemare
OffRL
62
166
0
13 Jan 2021
The Distracting Control Suite -- A Challenging Benchmark for
  Reinforcement Learning from Pixels
The Distracting Control Suite -- A Challenging Benchmark for Reinforcement Learning from Pixels
Austin Stone
Oscar Ramirez
K. Konolige
Rico Jonschkowski
161
101
0
07 Jan 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
...
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Percy Liang
OOD
128
1,406
0
14 Dec 2020
Planning from Pixels using Inverse Dynamics Models
Planning from Pixels using Inverse Dynamics Models
Keiran Paster
Sheila A. McIlraith
Jimmy Ba
BDL
27
41
0
04 Dec 2020
World Model as a Graph: Learning Latent Landmarks for Planning
World Model as a Graph: Learning Latent Landmarks for Planning
Lunjun Zhang
Ge Yang
Bradly C. Stadie
DRL
33
73
0
25 Nov 2020
C-Learning: Learning to Achieve Goals via Recursive Classification
C-Learning: Learning to Achieve Goals via Recursive Classification
Benjamin Eysenbach
Ruslan Salakhutdinov
Sergey Levine
OffRL
43
69
0
17 Nov 2020
A Geometric Perspective on Self-Supervised Policy Adaptation
A Geometric Perspective on Self-Supervised Policy Adaptation
Cristian Bodnar
Karol Hausman
Gabriel Dulac-Arnold
Rico Jonschkowski
SSL
48
5
0
14 Nov 2020
ROLL: Visual Self-Supervised Reinforcement Learning with Object
  Reasoning
ROLL: Visual Self-Supervised Reinforcement Learning with Object Reasoning
Yufei Wang
G. Narasimhan
Xingyu Lin
Brian Okorn
David Held
OffRL
LRM
39
14
0
13 Nov 2020
Goal-Aware Prediction: Learning to Model What Matters
Goal-Aware Prediction: Learning to Model What Matters
Suraj Nair
Silvio Savarese
Chelsea Finn
47
64
0
14 Jul 2020
Self-Supervised Policy Adaptation during Deployment
Self-Supervised Policy Adaptation during Deployment
Nicklas Hansen
Rishabh Jangir
Yu Sun
Guillem Alenyà
Pieter Abbeel
Alexei A. Efros
Lerrel Pinto
Xiaolong Wang
53
161
0
08 Jul 2020
Feature Alignment and Restoration for Domain Generalization and
  Adaptation
Feature Alignment and Restoration for Domain Generalization and Adaptation
Xin Jin
Cuiling Lan
Wenjun Zeng
Zhibo Chen
OOD
42
39
0
22 Jun 2020
Learning Invariant Representations for Reinforcement Learning without
  Reconstruction
Learning Invariant Representations for Reinforcement Learning without Reconstruction
Amy Zhang
R. McAllister
Roberto Calandra
Y. Gal
Sergey Levine
OOD
SSL
75
469
0
18 Jun 2020
Reinforcement Learning with Augmented Data
Reinforcement Learning with Augmented Data
Michael Laskin
Kimin Lee
Adam Stooke
Lerrel Pinto
Pieter Abbeel
A. Srinivas
OffRL
43
653
0
30 Apr 2020
Image Augmentation Is All You Need: Regularizing Deep Reinforcement
  Learning from Pixels
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels
Ilya Kostrikov
Denis Yarats
Rob Fergus
OffRL
61
779
0
28 Apr 2020
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic
  Reinforcement Learning
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning
Ryan Julian
Benjamin Swanson
Gaurav Sukhatme
Sergey Levine
Chelsea Finn
Karol Hausman
OnRL
CLL
45
43
0
21 Apr 2020
CURL: Contrastive Unsupervised Representations for Reinforcement
  Learning
CURL: Contrastive Unsupervised Representations for Reinforcement Learning
A. Srinivas
Michael Laskin
Pieter Abbeel
SSL
DRL
OffRL
73
1,073
0
08 Apr 2020
Weakly-Supervised Reinforcement Learning for Controllable Behavior
Weakly-Supervised Reinforcement Learning for Controllable Behavior
Lisa Lee
Benjamin Eysenbach
Ruslan Salakhutdinov
S. Gu
Chelsea Finn
SSL
44
26
0
06 Apr 2020
Invariant Causal Prediction for Block MDPs
Invariant Causal Prediction for Block MDPs
Amy Zhang
Clare Lyle
Shagun Sodhani
Angelos Filos
Marta Z. Kwiatkowska
Joelle Pineau
Y. Gal
Doina Precup
OffRL
AI4CE
OOD
62
139
0
12 Mar 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
144
18,523
0
13 Feb 2020
Generalizing to unseen domains via distribution matching
Generalizing to unseen domains via distribution matching
Isabela Albuquerque
João Monteiro
Mohammad Javad Darvishi Bayazi
T. Falk
Ioannis Mitliagkas
OOD
49
156
0
03 Nov 2019
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks
  via Visual Subgoal Generation
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation
Suraj Nair
Chelsea Finn
VGen
40
138
0
12 Sep 2019
Invariant Risk Minimization
Invariant Risk Minimization
Martín Arjovsky
Léon Bottou
Ishaan Gulrajani
David Lopez-Paz
OOD
135
2,190
0
05 Jul 2019
Exploration via Hindsight Goal Generation
Exploration via Hindsight Goal Generation
Zhizhou Ren
Kefan Dong
Yuanshuo Zhou
Qiang Liu
Jian-wei Peng
40
89
0
10 Jun 2019
DeepMDP: Learning Continuous Latent Space Models for Representation
  Learning
DeepMDP: Learning Continuous Latent Space Models for Representation Learning
Carles Gelada
Saurabh Kumar
Jacob Buckman
Ofir Nachum
Marc G. Bellemare
BDL
45
283
0
06 Jun 2019
Adversarial Invariant Feature Learning with Accuracy Constraint for
  Domain Generalization
Adversarial Invariant Feature Learning with Accuracy Constraint for Domain Generalization
K. Akuzawa
Yusuke Iwasawa
Y. Matsuo
OOD
33
77
0
29 Apr 2019
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning
Vitchyr H. Pong
Murtaza Dalal
Steven Lin
Ashvin Nair
Shikhar Bahl
Sergey Levine
OffRL
SSL
53
273
0
08 Mar 2019
Provably efficient RL with Rich Observations via Latent State Decoding
Provably efficient RL with Rich Observations via Latent State Decoding
S. Du
A. Krishnamurthy
Nan Jiang
Alekh Agarwal
Miroslav Dudík
John Langford
OffRL
29
230
0
25 Jan 2019
Assessing Generalization in Deep Reinforcement Learning
Assessing Generalization in Deep Reinforcement Learning
Charles Packer
Katelyn Gao
Jernej Kos
Philipp Krahenbuhl
V. Koltun
D. Song
OffRL
89
235
0
29 Oct 2018
Near-Optimal Representation Learning for Hierarchical Reinforcement
  Learning
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning
Ofir Nachum
S. Gu
Honglak Lee
Sergey Levine
49
208
0
02 Oct 2018
Visual Reinforcement Learning with Imagined Goals
Visual Reinforcement Learning with Imagined Goals
Ashvin Nair
Vitchyr H. Pong
Murtaza Dalal
Shikhar Bahl
Steven Lin
Sergey Levine
SSL
54
540
0
12 Jul 2018
Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal
  Exploration
Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal Exploration
Alexandre Péré
Sébastien Forestier
Olivier Sigaud
Pierre-Yves Oudeyer
SSL
DRL
18
95
0
02 Mar 2018
Addressing Function Approximation Error in Actor-Critic Methods
Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto
H. V. Hoof
David Meger
OffRL
132
5,121
0
26 Feb 2018
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement
  Learning with a Stochastic Actor
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
Tuomas Haarnoja
Aurick Zhou
Pieter Abbeel
Sergey Levine
172
8,236
0
04 Jan 2018
Hindsight Experience Replay
Hindsight Experience Replay
Marcin Andrychowicz
Dwight Crow
Alex Ray
Jonas Schneider
Rachel Fong
Peter Welinder
Bob McGrew
Joshua Tobin
Pieter Abbeel
Wojciech Zaremba
OffRL
216
2,307
0
05 Jul 2017
Automatic Goal Generation for Reinforcement Learning Agents
Automatic Goal Generation for Reinforcement Learning Agents
Carlos Florensa
David Held
Xinyang Geng
Pieter Abbeel
87
506
0
17 May 2017
The Variational Fair Autoencoder
The Variational Fair Autoencoder
Christos Louizos
Kevin Swersky
Yujia Li
Max Welling
R. Zemel
DRL
107
633
0
03 Nov 2015
Trust Region Policy Optimization
Trust Region Policy Optimization
John Schulman
Sergey Levine
Philipp Moritz
Michael I. Jordan
Pieter Abbeel
221
6,722
0
19 Feb 2015
FastMMD: Ensemble of Circular Discrepancy for Efficient Two-Sample Test
FastMMD: Ensemble of Circular Discrepancy for Efficient Two-Sample Test
Ji Zhao
Deyu Meng
54
98
0
12 May 2014
A Kernel Method for the Two-Sample Problem
A Kernel Method for the Two-Sample Problem
Arthur Gretton
Karsten Borgwardt
Malte J. Rasch
Bernhard Schölkopf
Alex Smola
129
2,348
0
15 May 2008
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