Selected papers are grouped by project and listed in a (non-chronological) order that makes for a coherent narrative.
Successor Features and Generalised Policy Improvement
            
            Successor Features for Transfer in Reinforcement Learning
André Barreto, Will Dabney, Rémi Munos, Jonathan J. Hunt, Tom Schaul, Hado van Hasselt, David Silver
 In Advances in Neural Information Processing Systems
              (NIPS), 2017 - selected as a spotlight
            
            [ pdf ] [ slides
            ] [poster
            ] [ workshop
              version ] [ more
              info ] Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement
André Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel Mankowitz, Augustin Žídek, Rémi Munos
In Proceedings of the International Conference on
              Machine Learning (ICML), 2018
            
            [ pdf ] [ video ] [ slides
              1 ] [ slides
              2 ] [ poster
            ] [ more
              info ]The Option Keyboard: Combining Skills in Reinforcement
              Learning
            
            André Barreto, Diana Borsa, Shaobo Hou, Gheorghe Comanici, Eser Aygün, Philippe Hamel, Daniel Toyama, Jonathan J. Hunt, Shibl Mourad, David Silver, Doina Precup
In Advances in Neural Information Processing Systems (NeurIPS)
[ pdf ] [ video ] [ slides ] [ poster ] [ more info ]Universal Successor Features Approximators
Diana Borsa, André Barreto, John Quan, Daniel Mankowitz, Rémi Munos, Hado van Hasselt, David Silver, Tom Schaul
In Proceedings of the International Conference on
              Learning Representations (ICLR), 2019
            
            [ pdf ] [ video 1 ] [ video 2 ] [ more info ]Composing Entropic Policies Using Divergence Correction
            
            Jonathan Hunt, André Barreto, Timothy Lillicrap, Nicolas Heess
In Proceedings of  International Conference on
              Machine Learning (ICML), 2019
            
            [
              pdf ] [ videos
            ] [ more
              info ]Fast Task Inference with Variational Intrinsic Successor
              Features
            
            Steven Hansen, Will Dabney, André Barreto, Tom Van de
              Wiele, David Warde-Farley, Volodymyr Mnih
            
            arXiv
[ pdf ] [ more info ]Stochastic Factorization
Computing the Stationary Distribution of a Finite Markov Chain Through Stochastic Factorization
André Barreto and Marcelo Fragoso
 SIAM Journal on Matrix Analysis and Applications, v.
              32, pp. 1513–1523, 2011
            
            [ pdf
            ] [ more
              info ]Lumping the States of a Finite Markov Chain Through Stochastic Factorization
André Barreto and Marcelo Fragoso
 In Proceedings of the World Congress of the
              International Federation of Automatic Control (IFAC), 2011
            
            [ pdf
            ] [ more
              info ]Policy Iteration Based on Stochastic Factorization
André Barreto, Joelle Pineau, Doina Precup
Journal of Artificial Intelligence Research, v. 50, pp. 763−803, 2014[ pdf ] [ more info ]