Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
Representation Matters: Improving Perception and Exploration for Robotics

Nov 03, 2020
Markus Wulfmeier, Arunkumar Byravan, Tim Hertweck, Irina Higgins, Ankush Gupta, Tejas Kulkarni, Malcolm Reynolds, Denis Teplyashin, Roland Hafner, Thomas Lampe, Martin Riedmiller


  Access Paper or Ask Questions

"What, not how": Solving an under-actuated insertion task from scratch

Oct 30, 2020
Giulia Vezzani, Michael Neunert, Markus Wulfmeier, Rae Jeong, Thomas Lampe, Noah Siegel, Roland Hafner, Abbas Abdolmaleki, Martin Riedmiller, Francesco Nori


  Access Paper or Ask Questions

Robust Constrained Reinforcement Learning for Continuous Control with Model Misspecification

Oct 20, 2020
Daniel J. Mankowitz, Dan A. Calian, Rae Jeong, Cosmin Paduraru, Nicolas Heess, Sumanth Dathathri, Martin Riedmiller, Timothy Mann


  Access Paper or Ask Questions

Local Search for Policy Iteration in Continuous Control

Oct 12, 2020
Jost Tobias Springenberg, Nicolas Heess, Daniel Mankowitz, Josh Merel, Arunkumar Byravan, Abbas Abdolmaleki, Jackie Kay, Jonas Degrave, Julian Schrittwieser, Yuval Tassa, Jonas Buchli, Dan Belov, Martin Riedmiller


  Access Paper or Ask Questions

Towards General and Autonomous Learning of Core Skills: A Case Study in Locomotion

Aug 06, 2020
Roland Hafner, Tim Hertweck, Philipp Klöppner, Michael Bloesch, Michael Neunert, Markus Wulfmeier, Saran Tunyasuvunakool, Nicolas Heess, Martin Riedmiller


  Access Paper or Ask Questions

Data-efficient Hindsight Off-policy Option Learning

Jul 30, 2020
Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala, Noah Siegel, Nicolas Heess, Martin Riedmiller


  Access Paper or Ask Questions

Simple Sensor Intentions for Exploration

May 15, 2020
Tim Hertweck, Martin Riedmiller, Michael Bloesch, Jost Tobias Springenberg, Noah Siegel, Markus Wulfmeier, Roland Hafner, Nicolas Heess


  Access Paper or Ask Questions

A Distributional View on Multi-Objective Policy Optimization

May 15, 2020
Abbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin Riedmiller


  Access Paper or Ask Questions

Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning

Feb 23, 2020
Noah Y. Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, Martin Riedmiller

* To appear in ICLR 2020 

  Access Paper or Ask Questions

Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics

Jan 02, 2020
Michael Neunert, Abbas Abdolmaleki, Markus Wulfmeier, Thomas Lampe, Jost Tobias Springenberg, Roland Hafner, Francesco Romano, Jonas Buchli, Nicolas Heess, Martin Riedmiller

* Presented at the 3rd Conference on Robot Learning (CoRL 2019), Osaka, Japan. Video: https://youtu.be/eUqQDLQXb7I 

  Access Paper or Ask Questions

Quinoa: a Q-function You Infer Normalized Over Actions

Nov 05, 2019
Jonas Degrave, Abbas Abdolmaleki, Jost Tobias Springenberg, Nicolas Heess, Martin Riedmiller

* Deep RL Workshop/NeurIPS 

  Access Paper or Ask Questions

Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models

Oct 09, 2019
Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Siegel, Nicolas Heess, Martin Riedmiller

* To appear at the 3rd annual Conference on Robot Learning, Osaka, Japan (CoRL 2019). 24 pages including appendix (main paper - 8 pages) 

  Access Paper or Ask Questions

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control

Sep 26, 2019
H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W. Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin Riedmiller, Matthew M. Botvinick

* * equal contribution 

  Access Paper or Ask Questions

Regularized Hierarchical Policies for Compositional Transfer in Robotics

Jun 27, 2019
Markus Wulfmeier, Abbas Abdolmaleki, Roland Hafner, Jost Tobias Springenberg, Michael Neunert, Tim Hertweck, Thomas Lampe, Noah Siegel, Nicolas Heess, Martin Riedmiller

* Preprint. Under review. Addressed typos 

  Access Paper or Ask Questions

Robust Reinforcement Learning for Continuous Control with Model Misspecification

Jun 18, 2019
Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Timothy Mann, Todd Hester, Martin Riedmiller


  Access Paper or Ask Questions

Simultaneously Learning Vision and Feature-based Control Policies for Real-world Ball-in-a-Cup

Feb 18, 2019
Devin Schwab, Tobias Springenberg, Murilo F. Martins, Thomas Lampe, Michael Neunert, Abbas Abdolmaleki, Tim Hertweck, Roland Hafner, Francesco Nori, Martin Riedmiller

* Videos can be found at https://sites.google.com/view/rss-2019-sawyer-bic/ 

  Access Paper or Ask Questions

Self-supervised Learning of Image Embedding for Continuous Control

Jan 03, 2019
Carlos Florensa, Jonas Degrave, Nicolas Heess, Jost Tobias Springenberg, Martin Riedmiller

* Contributed talk at Inference to Control workshop at NeurIPS2018 

  Access Paper or Ask Questions

Relative Entropy Regularized Policy Iteration

Dec 05, 2018
Abbas Abdolmaleki, Jost Tobias Springenberg, Jonas Degrave, Steven Bohez, Yuval Tassa, Dan Belov, Nicolas Heess, Martin Riedmiller


  Access Paper or Ask Questions

Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards

Oct 08, 2018
Mel Vecerik, Todd Hester, Jonathan Scholz, Fumin Wang, Olivier Pietquin, Bilal Piot, Nicolas Heess, Thomas Rothörl, Thomas Lampe, Martin Riedmiller


  Access Paper or Ask Questions

Maximum a Posteriori Policy Optimisation

Jun 14, 2018
Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Remi Munos, Nicolas Heess, Martin Riedmiller


  Access Paper or Ask Questions

Graph networks as learnable physics engines for inference and control

Jun 04, 2018
Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin Riedmiller, Raia Hadsell, Peter Battaglia

* ICML 2018 

  Access Paper or Ask Questions

Learning by Playing - Solving Sparse Reward Tasks from Scratch

Feb 28, 2018
Martin Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom Van de Wiele, Volodymyr Mnih, Nicolas Heess, Jost Tobias Springenberg

* A video of the rich set of learned behaviours can be found at https://youtu.be/mPKyvocNe_M 

  Access Paper or Ask Questions

DeepMind Control Suite

Jan 02, 2018
Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, Timothy Lillicrap, Martin Riedmiller

* 24 pages, 7 figures, 2 tables 

  Access Paper or Ask Questions

PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations

Jul 24, 2017
Rico Jonschkowski, Roland Hafner, Jonathan Scholz, Martin Riedmiller

* Accepted at Robotics: Science and Systems (RSS 2017) Workshop -- New Frontiers for Deep Learning in Robotics http://juxi.net/workshop/deep-learning-rss-2017/ 

  Access Paper or Ask Questions

Emergence of Locomotion Behaviours in Rich Environments

Jul 10, 2017
Nicolas Heess, Dhruva TB, Srinivasan Sriram, Jay Lemmon, Josh Merel, Greg Wayne, Yuval Tassa, Tom Erez, Ziyu Wang, S. M. Ali Eslami, Martin Riedmiller, David Silver


  Access Paper or Ask Questions

Data-efficient Deep Reinforcement Learning for Dexterous Manipulation

Apr 10, 2017
Ivaylo Popov, Nicolas Heess, Timothy Lillicrap, Roland Hafner, Gabriel Barth-Maron, Matej Vecerik, Thomas Lampe, Yuval Tassa, Tom Erez, Martin Riedmiller

* 12 pages, 5 Figures 

  Access Paper or Ask Questions

Learning and Transfer of Modulated Locomotor Controllers

Oct 17, 2016
Nicolas Heess, Greg Wayne, Yuval Tassa, Timothy Lillicrap, Martin Riedmiller, David Silver

* Supplemental video available at https://youtu.be/sboPYvhpraQ 

  Access Paper or Ask Questions

Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images

Nov 20, 2015
Manuel Watter, Jost Tobias Springenberg, Joschka Boedecker, Martin Riedmiller

* Final NIPS version 

  Access Paper or Ask Questions

Multimodal Deep Learning for Robust RGB-D Object Recognition

Aug 18, 2015
Andreas Eitel, Jost Tobias Springenberg, Luciano Spinello, Martin Riedmiller, Wolfram Burgard

* Final version submitted to IROS'2015, results unchanged, reformulation of some text passages in abstract and introduction 

  Access Paper or Ask Questions