A New Fast Accurate Nonlinear Medical Image Registration Program Including Surface Preserving Regularization. - Audrunas Gruslys; Julio Acosta-Cabronero; Peter J. Nestor; Guy B. Williams; Richard E. Ansorge (IEEE Trans. Medical Imaging, 2014)

Memory-Efficient Backpropagation Through Time. - Audrunas Gruslys; Rémi Munos; Ivo Danihelka; Marc Lanctot; Alex Graves (NIPS, 2016)

A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. - Marc Lanctot; Vinícius Flores Zambaldi; Audrunas Gruslys; Angeliki Lazaridou; Karl Tuyls; Julien Pérolat; David Silver; Thore Graepel (NIPS, 2017)

The Reactor: A Sample-Efficient Actor-Critic Architecture. - Audrunas Gruslys; Mohammad Gheshlaghi Azar; Marc G. Bellemare; Rémi Munos (CoRR, 2017)

Learning from Demonstrations for Real World Reinforcement Learning. - Todd Hester; Matej Vecerík; Olivier Pietquin; Marc Lanctot; Tom Schaul; Bilal Piot; Andrew Sendonaris; Gabriel Dulac-Arnold; Ian Osband; John P. Agapiou; Joel Z. Leibo; Audrunas Gruslys (CoRR, 2017)

Value-Decomposition Networks For Cooperative Multi-Agent Learning. - Peter Sunehag; Guy Lever; Audrunas Gruslys; Wojciech Marian Czarnecki; Vinícius Flores Zambaldi; Max Jaderberg; Marc Lanctot; Nicolas Sonnerat; Joel Z. Leibo; Karl Tuyls; Thore Graepel (CoRR, 2017)

Deep Q-learning From Demonstrations. - Todd Hester; Matej Vecerík; Olivier Pietquin; Marc Lanctot; Tom Schaul; Bilal Piot; Dan Horgan; John Quan; Andrew Sendonaris; Ian Osband; Gabriel Dulac-Arnold; John P. Agapiou; et al. (AAAI, 2018)

Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward. - Peter Sunehag; Guy Lever; Audrunas Gruslys; Wojciech Marian Czarnecki; Vinícius Flores Zambaldi; Max Jaderberg; Marc Lanctot; Nicolas Sonnerat; Joel Z. Leibo; Karl Tuyls; Thore Graepel (AAMAS, 2018)

The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning. - Audrunas Gruslys; Will Dabney; Mohammad Gheshlaghi Azar; Bilal Piot; Marc G. Bellemare; Rémi Munos (ICLR (Poster), 2018)

Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents. - Joel Z. Leibo; Cyprien de Masson d'Autume; Daniel Zoran; David Amos; Charles Beattie; Keith Anderson; Antonio García Castañeda; Manuel Sanchez; Simon Green; Audrunas Gruslys; Shane Legg; Demis Hassabis; et al. (CoRR, 2018)

Neural Replicator Dynamics. - Shayegan Omidshafiei; Daniel Hennes; Dustin Morrill; Rémi Munos; Julien Pérolat; Marc Lanctot; Audrunas Gruslys; Jean-Baptiste Lespiau; Karl Tuyls (CoRR, 2019)

Neural Replicator Dynamics: Multiagent Learning via Hedging Policy Gradients. - Daniel Hennes; Dustin Morrill; Shayegan Omidshafiei; Rémi Munos; Julien Pérolat; Marc Lanctot; Audrunas Gruslys; Jean-Baptiste Lespiau; Paavo Parmas; Edgar A. Duéñez-Guzmán; Karl Tuyls (AAMAS, 2020)

Fast computation of Nash Equilibria in Imperfect Information Games. - Rémi Munos; Julien Pérolat; Jean-Baptiste Lespiau; Mark Rowland 001; Bart De Vylder; Marc Lanctot; Finbarr Timbers; Daniel Hennes; Shayegan Omidshafiei; Audrunas Gruslys; Mohammad Gheshlaghi Azar; Edward Lockhart; et al. (ICML, 2020)

Navigating the Landscape of Games. - Shayegan Omidshafiei; Karl Tuyls; Wojciech M. Czarnecki; Francisco C. Santos; Mark Rowland 001; Jerome T. Connor; Daniel Hennes; Paul Muller; Julien Pérolat; Bart De Vylder; Audrunas Gruslys; Rémi Munos (CoRR, 2020)

The Advantage Regret-Matching Actor-Critic. - Audrunas Gruslys; Marc Lanctot; Rémi Munos; Finbarr Timbers; Martin Schmid; Julien Pérolat; Dustin Morrill; Vinícius Flores Zambaldi; Jean-Baptiste Lespiau; John Schultz; Mohammad Gheshlaghi Azar; Michael Bowling; et al. (CoRR, 2020)

Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning. - Julien Pérolat; Bart De Vylder; Daniel Hennes; Eugene Tarassov; Florian Strub; Vincent de Boer; Paul Muller; Jerome T. Connor; Neil Burch; Thomas W. Anthony 001; Stephen McAleer; Romuald Elie; et al. (CoRR, 2022)

Figure Data for the paper "Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning". - Julien Pérolat; Bart De Vylder; Daniel Hennes; Eugene Tarassov; Florian Strub; Vincent de Boer; Paul Muller; Jerome T. Connor; Neil Burch; Thomas Anthony 001; Stephen McAleer; Romuald Elie; et al. (Zenodo, 2022)

Quantile Credit Assignment. - Thomas Mesnard; Wenqi Chen; Alaa Saade; Yunhao Tang; Mark Rowland 001; Theophane Weber; Clare Lyle; Audrunas Gruslys; Michal Valko; Will Dabney; Georg Ostrovski; Eric Moulines; et al. (ICML, 2023)