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2004.14646
Cited By
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning
International Conference on Machine Learning (ICML), 2020
30 April 2020
Z. Guo
Bernardo Avila-Pires
Bilal Piot
Jean-Bastien Grill
Florent Altché
Rémi Munos
M. G. Azar
BDL
DRL
SSL
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Papers citing
"Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning"
50 / 99 papers shown
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Measuring In-Context Computation Complexity via Hidden State Prediction
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Towards General-Purpose Model-Free Reinforcement Learning
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Efficient Training of Large Vision Models via Advanced Automated Progressive Learning
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A Single Goal is All You Need: Skills and Exploration Emerge from Contrastive RL without Rewards, Demonstrations, or Subgoals
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Unsupervised Representation Learning by Balanced Self Attention Matching
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Simon Korman
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ProSpec RL: Plan Ahead, then Execute
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Huiyu Duan
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Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations
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Erdun Gao
Fan Feng
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Shikui Tu
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PoliFormer: Scaling On-Policy RL with Transformers Results in Masterful Navigators
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Kiana Ehsani
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Ross Girshick
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Luca Weihs
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Time-Series JEPA for Predictive Remote Control under Capacity-Limited Networks
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Mehdi Bennis
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Representation Learning For Efficient Deep Multi-Agent Reinforcement Learning
Dom Huh
Prasant Mohapatra
283
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A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning
Khimya Khetarpal
Z. Guo
Bernardo Avila-Pires
Yunhao Tang
Clare Lyle
Mark Rowland
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Diana Borsa
A. Guez
Will Dabney
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04 Jun 2024
Cross-Embodiment Robot Manipulation Skill Transfer using Latent Space Alignment
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Dwait Bhatt
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Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation
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Wanrong Zhu
Meng Fang
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Bridging State and History Representations: Understanding Self-Predictive RL
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Benjamin Eysenbach
Erfan Seyedsalehi
Michel Ma
Clement Gehring
Aditya Mahajan
Pierre-Luc Bacon
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Imitating Shortest Paths in Simulation Enables Effective Navigation and Manipulation in the Real World
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Kiana Ehsani
Tanmay Gupta
Rose Hendrix
Jordi Salvador
Luca Weihs
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Aniruddha Kembhavi
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Selective Visual Representations Improve Convergence and Generalization for Embodied AI
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Ever Evolving Evaluator (EV3): Towards Flexible and Reliable Meta-Optimization for Knowledge Distillation
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State Sequences Prediction via Fourier Transform for Representation Learning
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Mingxuan Ye
Yufei Kuang
Jie Wang
Rui Yang
Wen-gang Zhou
Houqiang Li
Feng Wu
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244
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24 Oct 2023
Representation Learning for Sequential Volumetric Design Tasks
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Yi Wang
Linh Tran
Chin-Yi Cheng
Jieliang Luo
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GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training
IEEE International Conference on Computer Vision (ICCV), 2023
Xi Deng
Han Shi
Runhu Huang
Changlin Li
Hang Xu
Jianhua Han
James T. Kwok
Shen Zhao
Wei Zhang
Xiaodan Liang
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231
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Crossway Diffusion: Improving Diffusion-based Visuomotor Policy via Self-supervised Learning
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Varun Belagali
Jinghuan Shang
Michael S. Ryoo
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Adrien Bolland
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381
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Bootstrapped Representations in Reinforcement Learning
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Charline Le Lan
Stephen Tu
Mark Rowland
Anna Harutyunyan
Rishabh Agarwal
Marc G. Bellemare
Will Dabney
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303
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Coarse Is Better? A New Pipeline Towards Self-Supervised Learning with Uncurated Images
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Ke Zhu
Yin He
Jianxin Wu
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Towards a Better Understanding of Representation Dynamics under TD-learning
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Rémi Munos
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Unlocking the Power of Representations in Long-term Novelty-based Exploration
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Alaa Saade
Steven Kapturowski
Daniele Calandriello
Charles Blundell
Pablo Sprechmann
Leopoldo Sarra
Oliver Groth
Michal Valko
Bilal Piot
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Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition
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Yash Chandak
S. Thakoor
Z. Guo
Yunhao Tang
Rémi Munos
Will Dabney
Diana Borsa
353
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Discovering Object-Centric Generalized Value Functions From Pixels
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Somjit Nath
G. Subbaraj
Khimya Khetarpal
Samira Ebrahimi Kahou
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ENTL: Embodied Navigation Trajectory Learner
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Klemen Kotar
Aaron Walsman
Roozbeh Mottaghi
454
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Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis
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Michael J. Mendelson
Nauman Ahad
Maks Sorokin
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Carolina Urzay
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255
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Unsupervised Representation Learning in Partially Observable Atari Games
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Deep Occupancy-Predictive Representations for Autonomous Driving
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Eivind Meyer
Lars Frederik Peiss
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375
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RePreM: Representation Pre-training with Masked Model for Reinforcement Learning
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Wei Shen
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Longbo Huang
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A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trends
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Jie Gui
Tuo Chen
Jing Zhang
Qiong Cao
Zhe Sun
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Understanding Self-Predictive Learning for Reinforcement Learning
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Deep Reinforcement Learning with Vector Quantized Encoding
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Efficient Deep Reinforcement Learning with Predictive Processing Proximal Policy Optimization
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Dynamic Memory-based Curiosity: A Bootstrap Approach for Exploration
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BYOL-Explore: Exploration by Bootstrapped Prediction
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Florent Altché
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Bilal Piot
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Contrastive Learning as Goal-Conditioned Reinforcement Learning
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Sergey Levine
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Learning Behavior Representations Through Multi-Timescale Bootstrapping
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Michael J. Mendelson
Maks Sorokin
S. Thakoor
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Eva L. Dyer
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