Volodymyr Mnih

Publication Activity (10 Years)

Years Active: 2006-2023
Publications (10 Years): 38

Top Topics

Reinforcement Learning

Top Venues

Publications

Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan A. Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih
In-context Reinforcement Learning with Algorithm Distillation. ICLR (2023)
Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Harris Chan, Gheorghe Comanici, Sebastian Flennerhag, Maxime Gazeau, Kristian Holsheimer, Dan Horgan, Michael Laskin, Clare Lyle, Hussain Masoom, Kay McKinney, Volodymyr Mnih, Alexander Neitz, Fabio Pardo, Jack Parker-Holder, John Quan, Tim Rocktäschel, Himanshu Sahni, Tom Schaul, Yannick Schroecker, Stephen Spencer, Richie Steigerwald, Luyu Wang, Lei Zhang
Vision-Language Models as a Source of Rewards. CoRR (2023)
Hao Liu, Tom Zahavy, Volodymyr Mnih, Satinder Singh
Palm up: Playing in the Latent Manifold for Unsupervised Pretraining. NeurIPS (2022)
DJ Strouse, Kate Baumli, David Warde-Farley, Volodymyr Mnih, Steven Stenberg Hansen
Learning more skills through optimistic exploration. ICLR (2022)
Hao Liu, Tom Zahavy, Volodymyr Mnih, Satinder Singh
Palm up: Playing in the Latent Manifold for Unsupervised Pretraining. CoRR (2022)
Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Hansen, Angelos Filos, Ethan A. Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih
In-context Reinforcement Learning with Algorithm Distillation. CoRR (2022)
Tom Zahavy, Brendan O'Donoghue, André Barreto, Volodymyr Mnih, Sebastian Flennerhag, Satinder Singh
Discovering Diverse Nearly Optimal Policies withSuccessor Features. CoRR (2021)
Ishan Durugkar, Steven Hansen, Stephen Spencer, Volodymyr Mnih
Wasserstein Distance Maximizing Intrinsic Control. CoRR (2021)
Steven Hansen, Guillaume Desjardins, Kate Baumli, David Warde-Farley, Nicolas Heess, Simon Osindero, Volodymyr Mnih
Entropic Desired Dynamics for Intrinsic Control. NeurIPS (2021)
Kate Baumli, David Warde-Farley, Steven Hansen, Volodymyr Mnih
Relative Variational Intrinsic Control. AAAI (2021)
Kate Baumli, David Warde-Farley, Steven Hansen, Volodymyr Mnih
Relative Variational Intrinsic Control. CoRR (2020)
Steven Hansen, Will Dabney, André Barreto, David Warde-Farley, Tom Van de Wiele, Volodymyr Mnih
Fast Task Inference with Variational Intrinsic Successor Features. ICLR (2020)
Tom Van de Wiele, David Warde-Farley, Andriy Mnih, Volodymyr Mnih
Q-Learning in enormous action spaces via amortized approximate maximization. CoRR (2020)
Steven Hansen, Will Dabney, André Barreto, Tom Van de Wiele, David Warde-Farley, Volodymyr Mnih
Fast Task Inference with Variational Intrinsic Successor Features. CoRR (2019)
Tejas D. Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih
Unsupervised Learning of Object Keypoints for Perception and Control. CoRR (2019)
David Warde-Farley, Tom Van de Wiele, Tejas D. Kulkarni, Catalin Ionescu, Steven Hansen, Volodymyr Mnih
Unsupervised Control Through Non-Parametric Discriminative Rewards. ICLR (Poster) (2019)
Tejas D. Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih
Unsupervised Learning of Object Keypoints for Perception and Control. NeurIPS (2019)
David Warde-Farley, Tom Van de Wiele, Tejas D. Kulkarni, Catalin Ionescu, Steven Hansen, Volodymyr Mnih
Unsupervised Control Through Non-Parametric Discriminative Rewards. CoRR (2018)
Brendan O'Donoghue, Ian Osband, Rémi Munos, Volodymyr Mnih
The Uncertainty Bellman Equation and Exploration. ICML (2018)
Lasse Espeholt, Hubert Soyer, Rémi Munos, Karen Simonyan, Volodymyr Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, Shane Legg, Koray Kavukcuoglu
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures. ICML (2018)
Lasse Espeholt, Hubert Soyer, Rémi Munos, Karen Simonyan, Volodymyr Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, Shane Legg, Koray Kavukcuoglu
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures. CoRR (2018)
Martin A. Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom Van de Wiele, Volodymyr Mnih, Nicolas Heess, Jost Tobias Springenberg
Learning by Playing - Solving Sparse Reward Tasks from Scratch. CoRR (2018)
Meire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot, Jacob Menick, Matteo Hessel, Ian Osband, Alex Graves, Volodymyr Mnih, Rémi Munos, Demis Hassabis, Olivier Pietquin, Charles Blundell, Shane Legg
Noisy Networks For Exploration. ICLR (Poster) (2018)
Brendan O'Donoghue, Rémi Munos, Koray Kavukcuoglu, Volodymyr Mnih
Combining policy gradient and Q-learning. ICLR (Poster) (2017)
Ziyu Wang, Victor Bapst, Nicolas Heess, Volodymyr Mnih, Rémi Munos, Koray Kavukcuoglu, Nando de Freitas
Sample Efficient Actor-Critic with Experience Replay. ICLR (Poster) (2017)
Brendan O'Donoghue, Ian Osband, Rémi Munos, Volodymyr Mnih
The Uncertainty Bellman Equation and Exploration. CoRR (2017)
Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, Koray Kavukcuoglu
Reinforcement Learning with Unsupervised Auxiliary Tasks. ICLR (2017)
Andrei A. Rusu, Sergio Gomez Colmenarejo, Çaglar Gülçehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, Raia Hadsell
Policy Distillation. ICLR (Poster) (2016)
Alexander Vezhnevets, Volodymyr Mnih, Simon Osindero, Alex Graves, Oriol Vinyals, John P. Agapiou, Koray Kavukcuoglu
Strategic Attentive Writer for Learning Macro-Actions. NIPS (2016)
Alexander Vezhnevets, Volodymyr Mnih, John P. Agapiou, Simon Osindero, Alex Graves, Oriol Vinyals, Koray Kavukcuoglu
Strategic Attentive Writer for Learning Macro-Actions. CoRR (2016)
Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu
Asynchronous Methods for Deep Reinforcement Learning. CoRR (2016)
Ziyu Wang, Victor Bapst, Nicolas Heess, Volodymyr Mnih, Rémi Munos, Koray Kavukcuoglu, Nando de Freitas
Sample Efficient Actor-Critic with Experience Replay. CoRR (2016)
Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, Koray Kavukcuoglu
Reinforcement Learning with Unsupervised Auxiliary Tasks. CoRR (2016)
Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu
Using Fast Weights to Attend to the Recent Past. NIPS (2016)
Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu
Asynchronous Methods for Deep Reinforcement Learning. ICML (2016)
Hado van Hasselt, Arthur Guez, Matteo Hessel, Volodymyr Mnih, David Silver
Learning values across many orders of magnitude. NIPS (2016)
Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu
Using Fast Weights to Attend to the Recent Past. CoRR (2016)
Brendan O'Donoghue, Rémi Munos, Koray Kavukcuoglu, Volodymyr Mnih
PGQ: Combining policy gradient and Q-learning. CoRR (2016)
Jimmy Ba, Volodymyr Mnih, Koray Kavukcuoglu
Multiple Object Recognition with Visual Attention. ICLR (Poster) (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)
Arun Nair, Praveen Srinivasan, Sam Blackwell, Cagdas Alcicek, Rory Fearon, Alessandro De Maria, Vedavyas Panneershelvam, Mustafa Suleyman, Charles Beattie, Stig Petersen, Shane Legg, Volodymyr Mnih, Koray Kavukcuoglu, David Silver
Massively Parallel Methods for Deep Reinforcement Learning. CoRR (2015)
Volodymyr Mnih, Nicolas Heess, Alex Graves, Koray Kavukcuoglu
Recurrent Models of Visual Attention. NIPS (2014)
Volodymyr Mnih, Nicolas Heess, Alex Graves, Koray Kavukcuoglu
Recurrent Models of Visual Attention. CoRR (2014)
Marc'Aurelio Ranzato, Volodymyr Mnih, Joshua M. Susskind, Geoffrey E. Hinton
Modeling Natural Images Using Gated MRFs. IEEE Trans. Pattern Anal. Mach. Intell. 35 (9) (2013)
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, Martin A. Riedmiller
Playing Atari with Deep Reinforcement Learning. CoRR (2013)
Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton
Conditional Restricted Boltzmann Machines for Structured Output Prediction CoRR (2012)
Volodymyr Mnih, Geoffrey E. Hinton
Learning to Label Aerial Images from Noisy Data. ICML (2012)
Marc'Aurelio Ranzato, Joshua M. Susskind, Volodymyr Mnih, Geoffrey E. Hinton
On deep generative models with applications to recognition. CVPR (2011)
Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton
Conditional Restricted Boltzmann Machines for Structured Output Prediction. UAI (2011)
Marc'Aurelio Ranzato, Volodymyr Mnih, Geoffrey E. Hinton
Generating more realistic images using gated MRF's. NIPS (2010)
Volodymyr Mnih, Geoffrey E. Hinton
Learning to Detect Roads in High-Resolution Aerial Images. ECCV (6) (2010)
Volodymyr Mnih, Csaba Szepesvári, Jean-Yves Audibert
Empirical Bernstein stopping. ICML (2008)
Xuming He, Richard S. Zemel, Volodymyr Mnih
Topological map learning from outdoor image sequences. J. Field Robotics 23 (11-12) (2006)