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Understanding Self-Predictive Learning for Reinforcement Learning

Understanding Self-Predictive Learning for Reinforcement Learning

6 December 2022
Yunhao Tang
Z. Guo
Pierre Harvey Richemond
Bernardo Avila-Pires
Yash Chandak
Rémi Munos
Mark Rowland
M. G. Azar
Charline Le Lan
Clare Lyle
András Gyorgy
S. Thakoor
Will Dabney
Bilal Piot
Daniele Calandriello
Michal Valko
    SSL
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Papers citing "Understanding Self-Predictive Learning for Reinforcement Learning"

10 / 10 papers shown
Title
seq-JEPA: Autoregressive Predictive Learning of Invariant-Equivariant World Models
seq-JEPA: Autoregressive Predictive Learning of Invariant-Equivariant World Models
Hafez Ghaemi
Eilif Muller
Shahab Bakhtiari
49
0
0
06 May 2025
Intrinsic Dynamics-Driven Generalizable Scene Representations for
  Vision-Oriented Decision-Making Applications
Intrinsic Dynamics-Driven Generalizable Scene Representations for Vision-Oriented Decision-Making Applications
Dayang Liang
Jinyang Lai
Yunlong Liu
31
0
0
30 May 2024
Cross-Domain Policy Adaptation by Capturing Representation Mismatch
Cross-Domain Policy Adaptation by Capturing Representation Mismatch
Jiafei Lyu
Chenjia Bai
Jingwen Yang
Zongqing Lu
Xiu Li
30
8
0
24 May 2024
PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis
PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis
Satoki Ishikawa
Makoto Yamada
Han Bao
Yuki Takezawa
66
0
0
23 May 2024
Bridging State and History Representations: Understanding
  Self-Predictive RL
Bridging State and History Representations: Understanding Self-Predictive RL
Tianwei Ni
Benjamin Eysenbach
Erfan Seyedsalehi
Michel Ma
Clement Gehring
Aditya Mahajan
Pierre-Luc Bacon
AI4TS
AI4CE
22
20
0
17 Jan 2024
Towards a Better Understanding of Representation Dynamics under
  TD-learning
Towards a Better Understanding of Representation Dynamics under TD-learning
Yunhao Tang
Rémi Munos
OffRL
23
1
0
29 May 2023
The Ladder in Chaos: A Simple and Effective Improvement to General DRL
  Algorithms by Policy Path Trimming and Boosting
The Ladder in Chaos: A Simple and Effective Improvement to General DRL Algorithms by Policy Path Trimming and Boosting
Hongyao Tang
M. Zhang
Jianye Hao
23
1
0
02 Mar 2023
Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments
Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments
Daniel Jarrett
Corentin Tallec
Florent Altché
Thomas Mesnard
Rémi Munos
Michal Valko
40
5
0
18 Nov 2022
Understanding self-supervised Learning Dynamics without Contrastive
  Pairs
Understanding self-supervised Learning Dynamics without Contrastive Pairs
Yuandong Tian
Xinlei Chen
Surya Ganguli
SSL
138
279
0
12 Feb 2021
Learning Successor States and Goal-Dependent Values: A Mathematical
  Viewpoint
Learning Successor States and Goal-Dependent Values: A Mathematical Viewpoint
Léonard Blier
Corentin Tallec
Yann Ollivier
46
30
0
18 Jan 2021
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