Georg Ostrovski

Publication Activity (10 Years)

Years Active: 2013-2023
Publications (10 Years): 32

Top Topics

Intrinsic Motivation

Reinforcement Learning

Credit Assignment

Top Venues

Publications

Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, André Barreto
Deep Reinforcement Learning with Plasticity Injection. CoRR (2023)
Mark Rowland, Rémi Munos, Mohammad Gheshlaghi Azar, Yunhao Tang, Georg Ostrovski, Anna Harutyunyan, Karl Tuyls, Marc G. Bellemare, Will Dabney
An Analysis of Quantile Temporal-Difference Learning. CoRR (2023)
Thomas Mesnard, Wenqi Chen, Alaa Saade, Yunhao Tang, Mark Rowland, Theophane Weber, Clare Lyle, Audrunas Gruslys, Michal Valko, Will Dabney, Georg Ostrovski, Eric Moulines, Rémi Munos
Quantile Credit Assignment. ICML (2023)
Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, André Barreto
Deep Reinforcement Learning with Plasticity Injection. NeurIPS (2023)
Tom Schaul, André Barreto, John Quan, Georg Ostrovski
The Phenomenon of Policy Churn. CoRR (2022)
Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matthew Hoffman, Razvan Pascanu, Arnaud Doucet
An empirical study of implicit regularization in deep offline RL. Trans. Mach. Learn. Res. 2022 (2022)
Tom Schaul, André Barreto, John Quan, Georg Ostrovski
The Phenomenon of Policy Churn. NeurIPS (2022)
Miruna Pislar, David Szepesvari, Georg Ostrovski, Diana L. Borsa, Tom Schaul
When should agents explore? ICLR (2022)
Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matt Hoffman, Razvan Pascanu, Arnaud Doucet
An Empirical Study of Implicit Regularization in Deep Offline RL. CoRR (2022)
Clare Lyle, Mark Rowland, Georg Ostrovski, Will Dabney
On the Effect of Auxiliary Tasks on Representation Dynamics. AISTATS (2021)
Georg Ostrovski, Pablo Samuel Castro, Will Dabney
The Difficulty of Passive Learning in Deep Reinforcement Learning. NeurIPS (2021)
Tom Schaul, Georg Ostrovski, Iurii Kemaev, Diana Borsa
Return-based Scaling: Yet Another Normalisation Trick for Deep RL. CoRR (2021)
Miruna Pislar, David Szepesvari, Georg Ostrovski, Diana Borsa, Tom Schaul
When should agents explore? CoRR (2021)
Will Dabney, Georg Ostrovski, André Barreto
Temporally-Extended ε-Greedy Exploration. ICLR (2021)
Georg Ostrovski, Pablo Samuel Castro, Will Dabney
The Difficulty of Passive Learning in Deep Reinforcement Learning. CoRR (2021)
Clare Lyle, Mark Rowland, Georg Ostrovski, Will Dabney
On The Effect of Auxiliary Tasks on Representation Dynamics. CoRR (2021)
Will Dabney, Georg Ostrovski, André Barreto
Temporally-Extended ε-Greedy Exploration. CoRR (2020)
Steven Kapturowski, Georg Ostrovski, John Quan, Rémi Munos, Will Dabney
Recurrent Experience Replay in Distributed Reinforcement Learning. ICLR (Poster) (2019)
Tom Schaul, Diana Borsa, David Ding, David Szepesvari, Georg Ostrovski, Will Dabney, Simon Osindero
Adapting Behaviour for Learning Progress. CoRR (2019)
Will Dabney, Georg Ostrovski, David Silver, Rémi Munos
Implicit Quantile Networks for Distributional Reinforcement Learning. CoRR (2018)
Georg Ostrovski, Will Dabney, Rémi Munos
Autoregressive Quantile Networks for Generative Modeling. CoRR (2018)
Georg Ostrovski, Will Dabney, Rémi Munos
Autoregressive Quantile Networks for Generative Modeling. ICML (2018)
Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver
Rainbow: Combining Improvements in Deep Reinforcement Learning. AAAI (2018)
Will Dabney, Georg Ostrovski, David Silver, Rémi Munos
Implicit Quantile Networks for Distributional Reinforcement Learning. ICML (2018)
Georg Ostrovski, Marc G. Bellemare, Aäron van den Oord, Rémi Munos
Count-Based Exploration with Neural Density Models. CoRR (2017)
Georg Ostrovski, Marc G. Bellemare, Aäron van den Oord, Rémi Munos
Count-Based Exploration with Neural Density Models. ICML (2017)
Karl Tuyls, Julien Pérolat, Marc Lanctot, Georg Ostrovski, Rahul Savani, Joel Z. Leibo, Toby Ord, Thore Graepel, Shane Legg
Symmetric Decomposition of Asymmetric Games. CoRR (2017)
Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Daniel Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver
Rainbow: Combining Improvements in Deep Reinforcement Learning. CoRR (2017)
Marc G. Bellemare, Georg Ostrovski, Arthur Guez, Philip S. Thomas, Rémi Munos
Increasing the Action Gap: New Operators for Reinforcement Learning. AAAI (2016)
Alex Graves, Greg Wayne, Malcolm Reynolds, Tim Harley, Ivo Danihelka, Agnieszka Grabska-Barwinska, Sergio Gomez Colmenarejo, Edward Grefenstette, Tiago Ramalho, John P. Agapiou, Adrià Puigdomènech Badia, Karl Moritz Hermann, Yori Zwols, Georg Ostrovski, Adam Cain, Helen King, Christopher Summerfield, Phil Blunsom, Koray Kavukcuoglu, Demis Hassabis
Hybrid computing using a neural network with dynamic external memory. Nat. 538 (7626) (2016)
Marc G. Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, Rémi Munos
Unifying Count-Based Exploration and Intrinsic Motivation. CoRR (2016)
Marc G. Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, Rémi Munos
Unifying Count-Based Exploration and Intrinsic Motivation. NIPS (2016)
Marc G. Bellemare, Georg Ostrovski, Arthur Guez, Philip S. Thomas, Rémi Munos
Increasing the Action Gap: New Operators for Reinforcement Learning. CoRR (2015)
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin A. Riedmiller, Andreas Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, Demis Hassabis
Human-level control through deep reinforcement learning. Nat. 518 (7540) (2015)
Georg Ostrovski, Sebastian van Strien
Payoff Performance of Fictitious Play. CoRR (2013)