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2406.04088
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Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2024
17 January 2025
Abdullah Akgul
Manuel Haußmann
M. Kandemir
OffRL
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Papers citing
"Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning"
44 / 44 papers shown
An Analytic Solution to Covariance Propagation in Neural Networks
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Yorie Nakahira
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24 Mar 2024
Simple Ingredients for Offline Reinforcement Learning
Edoardo Cetin
Andrea Tirinzoni
Matteo Pirotta
A. Lazaric
Yann Ollivier
Ahmed Touati
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319
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0
19 Mar 2024
Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting
International Conference on Learning Representations (ICLR), 2023
Zhang-Wei Hong
Pulkit Agrawal
Rémi Tachet des Combes
Romain Laroche
OffRL
202
25
0
22 Jun 2023
On the 1-Wasserstein Distance between Location-Scale Distributions and the Effect of Differential Privacy
Saurab Chhachhi
Fei Teng
234
9
0
28 Apr 2023
Model-Based Uncertainty in Value Functions
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Carlos E. Luis
A. Bottero
Julia Vinogradska
Felix Berkenkamp
Jan Peters
251
17
0
24 Feb 2023
Some Fundamental Aspects about Lipschitz Continuity of Neural Networks
International Conference on Learning Representations (ICLR), 2023
Grigory Khromov
Sidak Pal Singh
570
22
0
21 Feb 2023
Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization
International Conference on Learning Representations (ICLR), 2022
Jihwan Jeong
Xiaoyu Wang
Michael Gimelfarb
Hyunwoo J. Kim
Baher Abdulhai
Scott Sanner
OffRL
188
13
0
07 Oct 2022
Transformers are Sample-Efficient World Models
International Conference on Learning Representations (ICLR), 2022
Vincent Micheli
Eloi Alonso
Franccois Fleuret
VLM
OffRL
479
256
0
01 Sep 2022
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning
International Conference on Learning Representations (ICLR), 2022
Chenjia Bai
Lingxiao Wang
Zhuoran Yang
Zhihong Deng
Animesh Garg
Peng Liu
Zhaoran Wang
OffRL
266
156
0
23 Feb 2022
Adversarially Trained Actor Critic for Offline Reinforcement Learning
International Conference on Machine Learning (ICML), 2022
Ching-An Cheng
Tengyang Xie
Nan Jiang
Alekh Agarwal
OffRL
295
146
0
05 Feb 2022
Revisiting Design Choices in Offline Model-Based Reinforcement Learning
International Conference on Learning Representations (ICLR), 2021
Cong Lu
Philip J. Ball
Jack Parker-Holder
Michael A. Osborne
Stephen J. Roberts
OffRL
233
59
0
08 Oct 2021
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble
Gaon An
Seungyong Moon
Jang-Hyun Kim
Hyun Oh Song
OffRL
314
339
0
04 Oct 2021
Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage
Masatoshi Uehara
Wen Sun
OffRL
397
161
0
13 Jul 2021
Bellman-consistent Pessimism for Offline Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2021
Tengyang Xie
Ching-An Cheng
Nan Jiang
Paul Mineiro
Alekh Agarwal
OffRL
LRM
659
301
0
13 Jun 2021
A Minimalist Approach to Offline Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2021
Scott Fujimoto
S. Gu
OffRL
387
982
0
12 Jun 2021
Offline Reinforcement Learning as One Big Sequence Modeling Problem
Neural Information Processing Systems (NeurIPS), 2021
Michael Janner
Qiyang Li
Sergey Levine
OffRL
645
787
0
03 Jun 2021
Offline Reinforcement Learning with Fisher Divergence Critic Regularization
International Conference on Machine Learning (ICML), 2021
Ilya Kostrikov
Jonathan Tompson
Rob Fergus
Ofir Nachum
OffRL
307
336
0
14 Mar 2021
COMBO: Conservative Offline Model-Based Policy Optimization
Neural Information Processing Systems (NeurIPS), 2021
Tianhe Yu
Aviral Kumar
Rafael Rafailov
Aravind Rajeswaran
Sergey Levine
Chelsea Finn
OffRL
622
476
0
16 Feb 2021
Is Pessimism Provably Efficient for Offline RL?
International Conference on Machine Learning (ICML), 2020
Ying Jin
Zhuoran Yang
Zhaoran Wang
OffRL
617
389
0
30 Dec 2020
COG: Connecting New Skills to Past Experience with Offline Reinforcement Learning
Avi Singh
Albert Yu
Jonathan Yang
Jesse Zhang
Aviral Kumar
Sergey Levine
SSL
OffRL
OnRL
266
109
0
27 Oct 2020
Selective Dyna-style Planning Under Limited Model Capacity
Zaheer Abbas
Samuel Sokota
Erin J. Talvitie
Martha White
302
35
0
05 Jul 2020
A Deterministic Approximation to Neural SDEs
Andreas Look
M. Kandemir
Barbara Rakitsch
Jan Peters
DiffM
488
5
0
16 Jun 2020
Conservative Q-Learning for Offline Reinforcement Learning
Aviral Kumar
Aurick Zhou
George Tucker
Sergey Levine
OffRL
OnRL
432
2,196
0
08 Jun 2020
MOPO: Model-based Offline Policy Optimization
Neural Information Processing Systems (NeurIPS), 2020
Tianhe Yu
G. Thomas
Lantao Yu
Stefano Ermon
James Zou
Sergey Levine
Chelsea Finn
Tengyu Ma
OffRL
649
861
0
27 May 2020
MOReL : Model-Based Offline Reinforcement Learning
Rahul Kidambi
Aravind Rajeswaran
Praneeth Netrapalli
Thorsten Joachims
OffRL
457
751
0
12 May 2020
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine
Aviral Kumar
George Tucker
Justin Fu
OffRL
GP
1.0K
2,346
0
04 May 2020
D4RL: Datasets for Deep Data-Driven Reinforcement Learning
Justin Fu
Aviral Kumar
Ofir Nachum
George Tucker
Sergey Levine
GP
OffRL
1.1K
1,605
0
15 Apr 2020
Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning
International Conference on Learning Representations (ICLR), 2020
Noah Y. Siegel
Jost Tobias Springenberg
Felix Berkenkamp
A. Abdolmaleki
Michael Neunert
Thomas Lampe
Agrim Gupta
Nicolas Heess
Martin Riedmiller
OffRL
231
292
0
19 Feb 2020
Behavior Regularized Offline Reinforcement Learning
Yifan Wu
George Tucker
Ofir Nachum
OffRL
465
764
0
26 Nov 2019
Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
Xue Bin Peng
Aviral Kumar
Grace Zhang
Sergey Levine
OffRL
750
681
0
01 Oct 2019
Deep Active Learning with Adaptive Acquisition
International Joint Conference on Artificial Intelligence (IJCAI), 2019
Manuel Haussmann
Fred Hamprecht
M. Kandemir
187
41
0
27 Jun 2019
When to Trust Your Model: Model-Based Policy Optimization
Neural Information Processing Systems (NeurIPS), 2019
Michael Janner
Justin Fu
Marvin Zhang
Sergey Levine
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372
1,081
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19 Jun 2019
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction
Neural Information Processing Systems (NeurIPS), 2019
Aviral Kumar
Justin Fu
George Tucker
Sergey Levine
OffRL
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364
1,180
0
03 Jun 2019
Learning When-to-Treat Policies
Journal of the American Statistical Association (JASA), 2019
Xinkun Nie
Emma Brunskill
Stefan Wager
CML
OffRL
238
98
0
23 May 2019
Soft Actor-Critic Algorithms and Applications
Tuomas Haarnoja
Aurick Zhou
Kristian Hartikainen
George Tucker
Sehoon Ha
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Henry Zhu
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Off-Policy Deep Reinforcement Learning without Exploration
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07 Dec 2018
Lightweight Probabilistic Deep Networks
Jochen Gast
Stefan Roth
UQCV
OOD
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224
196
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29 May 2018
Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning
Vladimir Feinberg
Alvin Wan
Ion Stoica
Sai Li
Joseph E. Gonzalez
Sergey Levine
OffRL
293
334
0
28 Feb 2018
Addressing Function Approximation Error in Actor-Critic Methods
International Conference on Machine Learning (ICML), 2018
Scott Fujimoto
H. V. Hoof
David Meger
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797
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A Note on Concentration Inequalities for U-Statistics
Yannik Pitcan
80
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The Uncertainty Bellman Equation and Exploration
Brendan O'Donoghue
Ian Osband
Rémi Munos
Volodymyr Mnih
316
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Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
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Alexander Pritzel
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