DeepMDP: Learning Continuous Latent Space Models for Representation Learning

6 June 2019

Papers citing "DeepMDP: Learning Continuous Latent Space Models for Representation Learning"

44 / 94 papers shown

Title
DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations Fei Deng Ingook Jang Sungjin Ahn VLM 29 62 0 27 Oct 2021
Learning Domain Invariant Representations in Goal-conditioned Block MDPs Beining Han Chongyi Zheng Harris Chan Keiran Paster Michael Ruogu Zhang Jimmy Ba OOD AI4CE 20 13 0 27 Oct 2021
Planning from Pixels in Environments with Combinatorially Hard Search Spaces Marco Bagatella Miroslav Olsák Michal Rolínek Georg Martius OffRL 26 6 0 12 Oct 2021
Action-Sufficient State Representation Learning for Control with Structural Constraints Erdun Gao Chaochao Lu Liu Leqi José Miguel Hernández-Lobato Clark Glymour Bernhard Schölkopf Kun Zhang 59 32 0 12 Oct 2021
Neural Algorithmic Reasoners are Implicit Planners Andreea Deac Petar Velivcković Ognjen Milinković Pierre-Luc Bacon Jian Tang Mladen Nikolic OffRL 45 23 0 11 Oct 2021
How to Sense the World: Leveraging Hierarchy in Multimodal Perception for Robust Reinforcement Learning Agents Miguel Vasco Hang Yin Francisco S. Melo Ana Paiva 34 7 0 07 Oct 2021
Robust Predictable Control Benjamin Eysenbach Ruslan Salakhutdinov Sergey Levine OffRL 32 44 0 07 Sep 2021
Visual Adversarial Imitation Learning using Variational Models Rafael Rafailov Tianhe Yu Aravind Rajeswaran Chelsea Finn SSL 30 49 0 16 Jul 2021
Low-Dimensional State and Action Representation Learning with MDP Homomorphism Metrics N. Botteghi M. Poel B. Sirmaçek C. Brune 24 3 0 04 Jul 2021
Learning Task Informed Abstractions Xiang Fu Ge Yang Pulkit Agrawal Tommi Jaakkola 34 65 0 29 Jun 2021
Which Mutual-Information Representation Learning Objectives are Sufficient for Control? Kate Rakelly Abhishek Gupta Carlos Florensa Sergey Levine SSL 26 39 0 14 Jun 2021
Meta-Adaptive Nonlinear Control: Theory and Algorithms Guanya Shi Kamyar Azizzadenesheli Michael O'Connell Soon-Jo Chung Yisong Yue 31 41 0 11 Jun 2021
Learning Markov State Abstractions for Deep Reinforcement Learning Cameron Allen Neev Parikh Omer Gottesman George Konidaris BDL OffRL 42 36 0 08 Jun 2021
MICo: Improved representations via sampling-based state similarity for Markov decision processes Pablo Samuel Castro Tyler Kastner Prakash Panangaden Mark Rowland 48 35 0 03 Jun 2021
Offline Reinforcement Learning with Pseudometric Learning Robert Dadashi Shideh Rezaeifar Nino Vieillard Léonard Hussenot Olivier Pietquin M. Geist OffRL 39 40 0 02 Mar 2021
HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving Sirui Xie Xiaojian Ma Peiyu Yu Yixin Zhu Ying Nian Wu Song-Chun Zhu 42 20 0 22 Feb 2021
Uncertainty Maximization in Partially Observable Domains: A Cognitive Perspective Mirza Ramicic Andrea Bonarini 21 3 0 22 Feb 2021
Return-Based Contrastive Representation Learning for Reinforcement Learning Guoqing Liu Chuheng Zhang Li Zhao Tao Qin Jinhua Zhu Jian Li Nenghai Yu Tie-Yan Liu SSL OffRL 19 47 0 22 Feb 2021
Model-free Representation Learning and Exploration in Low-rank MDPs Aditya Modi Jinglin Chen A. Krishnamurthy Nan Jiang Alekh Agarwal OffRL 102 78 0 14 Feb 2021
DeepKoCo: Efficient latent planning with a task-relevant Koopman representation B. V. D. Heijden L. Ferranti Jens Kober Robert Babuška 21 6 0 25 Nov 2020
A Geometric Perspective on Self-Supervised Policy Adaptation Cristian Bodnar Karol Hausman Gabriel Dulac-Arnold Rico Jonschkowski SSL 44 5 0 14 Nov 2020
MELD: Meta-Reinforcement Learning from Images via Latent State Models Tony Zhao Anusha Nagabandi Kate Rakelly Chelsea Finn Sergey Levine OffRL 32 36 0 26 Oct 2020
Novelty Search in Representational Space for Sample Efficient Exploration Ruo Yu Tao Vincent François-Lavet Joelle Pineau 35 43 0 28 Sep 2020
Predictive Information Accelerates Learning in RL Kuang-Huei Lee Ian S. Fischer Anthony Z. Liu Yijie Guo Honglak Lee John F. Canny S. Guadarrama 23 72 0 24 Jul 2020
Learning Robust State Abstractions for Hidden-Parameter Block MDPs Amy Zhang Shagun Sodhani Khimya Khetarpal Joelle Pineau 31 5 0 14 Jul 2020
Data-Efficient Reinforcement Learning with Self-Predictive Representations Max Schwarzer Ankesh Anand Rishab Goel R. Devon Hjelm Aaron Courville Philip Bachman 41 312 0 12 Jul 2020
Learning Invariant Representations for Reinforcement Learning without Reconstruction Amy Zhang R. McAllister Roberto Calandra Y. Gal Sergey Levine OOD SSL 60 464 0 18 Jun 2020
Agent Modelling under Partial Observability for Deep Reinforcement Learning Georgios Papoudakis Filippos Christianos Stefano V. Albrecht 24 61 0 16 Jun 2020
Deep Reinforcement and InfoMax Learning Bogdan Mazoure Rémi Tachet des Combes T. Doan Philip Bachman R. Devon Hjelm AI4CE 27 108 0 12 Jun 2020
Primal Wasserstein Imitation Learning Robert Dadashi Léonard Hussenot M. Geist Olivier Pietquin 26 124 0 08 Jun 2020
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning Z. Guo Bernardo Avila-Pires Bilal Piot Jean-Bastien Grill Florent Altché Rémi Munos M. G. Azar BDL DRL SSL 43 140 0 30 Apr 2020
Weakly-Supervised Reinforcement Learning for Controllable Behavior Lisa Lee Benjamin Eysenbach Ruslan Salakhutdinov S. Gu Chelsea Finn SSL 22 26 0 06 Apr 2020
Neuroevolution of Self-Interpretable Agents Yujin Tang Duong Nguyen David R Ha 32 111 0 18 Mar 2020
Plannable Approximations to MDP Homomorphisms: Equivariance under Actions Elise van der Pol Thomas Kipf F. Oliehoek Max Welling 25 77 0 27 Feb 2020
Value-driven Hindsight Modelling A. Guez Fabio Viola T. Weber Lars Buesing Steven Kapturowski Doina Precup David Silver N. Heess OffRL 32 12 0 19 Feb 2020
Deep Representation Learning in Speech Processing: Challenges, Recent Advances, and Future Trends S. Latif R. Rana Sara Khalifa Raja Jurdak Junaid Qadir Björn W. Schuller AI4TS 37 81 0 02 Jan 2020
Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models Arunkumar Byravan Jost Tobias Springenberg A. Abdolmaleki Roland Hafner Michael Neunert Thomas Lampe Noah Y. Siegel N. Heess Martin Riedmiller OffRL 17 41 0 09 Oct 2019
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images Denis Yarats Amy Zhang Ilya Kostrikov Brandon Amos Joelle Pineau Rob Fergus DRL 65 441 0 02 Oct 2019
The Differentiable Cross-Entropy Method Brandon Amos Denis Yarats 34 54 0 27 Sep 2019
A Sufficient Statistic for Influence in Structured Multiagent Environments F. Oliehoek Stefan J. Witwicki L. Kaelbling 23 23 0 22 Jul 2019
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model Alex X. Lee Anusha Nagabandi Pieter Abbeel Sergey Levine OffRL BDL 36 372 0 01 Jul 2019
Combating the Compounding-Error Problem with a Multi-step Model Kavosh Asadi Dipendra Kumar Misra Seungchan Kim Michel L. Littman LRM 16 55 0 30 May 2019
Successor Features Combine Elements of Model-Free and Model-based Reinforcement Learning Lucas Lehnert Michael L. Littman 29 10 0 31 Jan 2019
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 283 1,401 0 01 Dec 2016