Decoding arm and hand movements across layers of the macaque frontal cortices. - Yan Tat Wong; Mariana Vigeral; David Putrino; David Pfau; Josh Merel; Liam Paninski; Bijan Pesaran (EMBC, 2012)

Bayesian spike inference from calcium imaging data. - Eftychios A. Pnevmatikakis; Josh Merel; Ari Pakman; Liam Paninski (ACSSC, 2013)

A multi-agent control framework for co-adaptation in brain-computer interfaces. - Josh Merel; Roy Fox; Tony Jebara; Liam Paninski (NIPS, 2013)

Encoder-Decoder Optimization for Brain-Computer Interfaces. - Josh Merel; Donald M. Pianto; John P. Cunningham; Liam Paninski (PLoS Comput. Biol., 2015)

Neuroprosthetic Decoder Training as Imitation Learning. - Josh Merel; David E. Carlson; Liam Paninski; John P. Cunningham (PLoS Comput. Biol., 2016)

New perspectives on learning, inference, and control in brains and machines. - Joshua Scott Merel (2016)

Multilayer Recurrent Network Models of Primate Retinal Ganglion Cell Responses. - Eleanor Batty; Josh Merel; Nora Brackbill; Alexander Heitman; Alexander Sher; Alan M. Litke; E. J. Chichilnisky; Liam Paninski (ICLR (Poster), 2017)

Robust Imitation of Diverse Behaviors. - Ziyu Wang 001; Josh Merel; Scott E. Reed; Nando de Freitas; Gregory Wayne; Nicolas Heess (NIPS, 2017)

Emergence of Locomotion Behaviours in Rich Environments. - Nicolas Heess; Dhruva TB; Srinivasan Sriram; Jay Lemmon; Josh Merel; Greg Wayne; Yuval Tassa; Tom Erez; Ziyu Wang 001; S. M. Ali Eslami; Martin A. Riedmiller; David Silver (CoRR, 2017)

Learning human behaviors from motion capture by adversarial imitation. - Josh Merel; Yuval Tassa; Dhruva TB; Sriram Srinivasan 005; Jay Lemmon; Ziyu Wang 001; Greg Wayne; Nicolas Heess (CoRR, 2017)

Graph Networks as Learnable Physics Engines for Inference and Control. - Alvaro Sanchez-Gonzalez; Nicolas Heess; Jost Tobias Springenberg; Josh Merel; Martin A. Riedmiller; Raia Hadsell; Peter W. Battaglia (ICML, 2018)

Reinforcement and Imitation Learning for Diverse Visuomotor Skills. - Yuke Zhu; Ziyu Wang 001; Josh Merel; Andrei A. Rusu; Tom Erez; Serkan Cabi; Saran Tunyasuvunakool; János Kramár; Raia Hadsell; Nando de Freitas; Nicolas Heess (Robotics: Science and Systems, 2018)

DeepMind Control Suite. - Yuval Tassa; Yotam Doron; Alistair Muldal; Tom Erez; Yazhe Li; Diego de Las Casas; David Budden; Abbas Abdolmaleki; Josh Merel; Andrew Lefrancq; Timothy P. Lillicrap; Martin A. Riedmiller (CoRR, 2018)

Emergent Coordination Through Competition. - Siqi Liu 002; Guy Lever; Josh Merel; Saran Tunyasuvunakool; Nicolas Heess; Thore Graepel (ICLR (Poster), 2019)

Hierarchical Visuomotor Control of Humanoids. - Josh Merel; Arun Ahuja; Vu Pham; Saran Tunyasuvunakool; Siqi Liu 002; Dhruva Tirumala; Nicolas Heess; Greg Wayne (ICLR (Poster), 2019)

Neural Probabilistic Motor Primitives for Humanoid Control. - Josh Merel; Leonard Hasenclever; Alexandre Galashov; Arun Ahuja; Vu Pham; Greg Wayne; Yee Whye Teh; Nicolas Heess (ICLR (Poster), 2019)

Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems. - Peter Sunehag; Guy Lever; Siqi Liu 002; Josh Merel; Nicolas Heess; Joel Z. Leibo; Edward Hughes 001; Tom Eccles; Thore Graepel (ALIFE, 2019)

Reusable neural skill embeddings for vision-guided whole body movement and object manipulation. - Josh Merel; Saran Tunyasuvunakool; Arun Ahuja; Yuval Tassa; Leonard Hasenclever; Vu Pham; Tom Erez; Greg Wayne; Nicolas Heess (CoRR, 2019)

Deep neuroethology of a virtual rodent. - Josh Merel; Diego Aldarondo; Jesse Marshall; Yuval Tassa; Greg Wayne; Bence Olveczky (ICLR, 2020)

CoMic: Complementary Task Learning & Mimicry for Reusable Skills. - Leonard Hasenclever; Fabio Pardo; Raia Hadsell; Nicolas Heess; Josh Merel (ICML, 2020)

Critic Regularized Regression. - Ziyu Wang 001; Alexander Novikov 001; Konrad Zolna; Josh Merel; Jost Tobias Springenberg; Scott E. Reed; Bobak Shahriari; Noah Y. Siegel; Çaglar Gülçehre; Nicolas Heess; Nando de Freitas (NeurIPS, 2020)

RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. - Çaglar Gülçehre; Ziyu Wang 001; Alexander Novikov 001; Thomas Paine; Sergio Gómez Colmenarejo; Konrad Zolna; Rishabh Agarwal; Josh Merel; Daniel J. Mankowitz; Cosmin Paduraru; Gabriel Dulac-Arnold; Jerry Li; et al. (NeurIPS, 2020)

Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning. - Giambattista Parascandolo; Lars Buesing; Josh Merel; Leonard Hasenclever; John Aslanides; Jessica B. Hamrick; Nicolas Heess; Alexander Neitz; Theophane Weber (CoRR, 2020)

RL Unplugged: Benchmarks for Offline Reinforcement Learning. - Çaglar Gülçehre; Ziyu Wang 001; Alexander Novikov 001; Tom Le Paine; Sergio Gómez Colmenarejo; Konrad Zolna; Rishabh Agarwal; Josh Merel; Daniel J. Mankowitz; Cosmin Paduraru; Gabriel Dulac-Arnold; Jerry Li; et al. (CoRR, 2020)

Learning to swim in potential flow. - Yusheng Jiao; Feng Ling; Sina Heydari; Nicolas Heess; Josh Merel; Eva Kanso (CoRR, 2020)

Local Search for Policy Iteration in Continuous Control. - Jost Tobias Springenberg; Nicolas Heess; Daniel J. Mankowitz; Josh Merel; Arunkumar Byravan; Abbas Abdolmaleki; Jackie Kay; Jonas Degrave; Julian Schrittwieser; Yuval Tassa; Jonas Buchli; Dan Belov; et al. (CoRR, 2020)

dm_control: Software and tasks for continuous control. - Saran Tunyasuvunakool; Alistair Muldal; Yotam Doron; Siqi Liu 002; Steven Bohez; Josh Merel; Tom Erez; Timothy P. Lillicrap; Nicolas Heess; Yuval Tassa (Softw. Impacts, 2020)

Catch & Carry: reusable neural controllers for vision-guided whole-body tasks. - Josh Merel; Saran Tunyasuvunakool; Arun Ahuja; Yuval Tassa; Leonard Hasenclever; Vu Pham; Tom Erez; Greg Wayne; Nicolas Heess (ACM Trans. Graph., 2020)

MyoChallenge 2022: Learning contact-rich manipulation using a musculoskeletal hand. - Vittorio Caggiano; Guillaume Durandau; Huawei Wang 003; Alberto Silvio Chiappa; Alexander Mathis; Pablo Tano; Nisheet Patel; Alexandre Pouget; Pierre Schumacher; Georg Martius; Daniel F. B. Haeufle; Yiran Geng; et al. (NeurIPS (Competition and Demos), 2021)

Learning Dynamics Models for Model Predictive Agents. - Michael Lutter; Leonard Hasenclever; Arunkumar Byravan; Gabriel Dulac-Arnold; Piotr Trochim; Nicolas Heess; Josh Merel; Yuval Tassa (CoRR, 2021)

Divergent representations of ethological visual inputs emerge from supervised, unsupervised, and reinforcement learning. - Grace W. Lindsay; Josh Merel; Tom Mrsic-Flogel; Maneesh Sahani (CoRR, 2021)

Evaluating Model-Based Planning and Planner Amortization for Continuous Control. - Arunkumar Byravan; Leonard Hasenclever; Piotr Trochim; Mehdi Mirza; Alessandro Davide Ialongo; Yuval Tassa; Jost Tobias Springenberg; Abbas Abdolmaleki; Nicolas Heess; Josh Merel; Martin A. Riedmiller (ICLR, 2022)

NeuPL: Neural Population Learning. - Siqi Liu 002; Luke Marris; Daniel Hennes; Josh Merel; Nicolas Heess; Thore Graepel (ICLR, 2022)

Learning transferable motor skills with hierarchical latent mixture policies. - Dushyant Rao; Fereshteh Sadeghi; Leonard Hasenclever; Markus Wulfmeier; Martina Zambelli; Giulia Vezzani; Dhruva Tirumala; Yusuf Aytar; Josh Merel; Nicolas Heess; Raia Hadsell (ICLR, 2022)

Data augmentation for efficient learning from parametric experts. - Alexandre Galashov; Joshua Scott Merel; Nicolas Heess (NeurIPS, 2022)

Imitate and Repurpose: Learning Reusable Robot Movement Skills From Human and Animal Behaviors. - Steven Bohez; Saran Tunyasuvunakool; Philemon Brakel; Fereshteh Sadeghi; Leonard Hasenclever; Yuval Tassa; Emilio Parisotto; Jan Humplik; Tuomas Haarnoja; Roland Hafner; Markus Wulfmeier; Michael Neunert; et al. (CoRR, 2022)

From motor control to team play in simulated humanoid football. - Siqi Liu 002; Guy Lever; Zhe Wang 055; Josh Merel; S. M. Ali Eslami; Daniel Hennes; Wojciech M. Czarnecki; Yuval Tassa; Shayegan Omidshafiei; Abbas Abdolmaleki; Noah Y. Siegel; Leonard Hasenclever; et al. (Sci. Robotics, 2022)

Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football". - Siqi Liu 002; Guy Lever; Zhe Wang 055; Josh Merel; S. M. Ali Eslami; Daniel Hennes; Wojciech Czarnecki 001; Yuval Tassa; Shayegan Omidshafiei; Abbas Abdolmaleki; Noah Y. Siegel; Leonard Hasenclever; et al. (Zenodo, 2022)

Universal Humanoid Motion Representations for Physics-Based Control. - Zhengyi Luo 002; Jinkun Cao; Josh Merel; Alexander Winkler; Jing Huang 020; Kris M. Kitani; Weipeng Xu (ICLR, 2024)

emg2pose: A Large and Diverse Benchmark for Surface Electromyographic Hand Pose Estimation. - Sasha Salter; Richard Warren; Collin Schlager; Adrian Spurr; Shangchen Han; Rohin Bhasin; Yujun Cai; Peter Walkington; Anuoluwapo Bolarinwa; Robert Wang 002; Nathan Danielson; Josh Merel; et al. (NeurIPS, 2024)

Deep Dive into Model-free Reinforcement Learning for Biological and Robotic Systems: Theory and Practice. - Yusheng Jiao; Feng Ling; Sina Heydari; Nicolas Heess; Josh Merel; Eva Kanso (CoRR, 2024)