Volodymyr Mnih

58 papers A* 16A 1Journal 28Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	ElasticTok: Adaptive Tokenization for Image and Video. ICLR Wilson Yan, Volodymyr Mnih, Aleksandra Faust, Matei Zaharia, Pieter Abbeel, Hao Liu
2025	A*	`conf`	LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations. ICML Anian Ruoss, Fabio Pardo, Harris Chan, Bonnie Li, Volodymyr Mnih, Tim Genewein
2024	J	`jnl`	ElasticTok: Adaptive Tokenization for Image and Video. CoRR Wilson Yan, Matei Zaharia, Volodymyr Mnih, Pieter Abbeel, Aleksandra Faust, Hao Liu
2024	J	`jnl`	LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations. CoRR Anian Ruoss, Fabio Pardo, Harris Chan, Bonnie Li, Volodymyr Mnih, Tim Genewein
2023	A*	`conf`	In-context Reinforcement Learning with Algorithm Distillation. ICLR Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih
2023	J	`jnl`	Vision-Language Models as a Source of Rewards. CoRR 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
2022	J	`jnl`	In-context Reinforcement Learning with Algorithm Distillation. CoRR Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih
2022	A*	`conf`	Learning more skills through optimistic exploration. ICLR DJ Strouse, Kate Baumli, David Warde-Farley, Volodymyr Mnih, Steven Stenberg Hansen
2022	A*	`conf`	Palm up: Playing in the Latent Manifold for Unsupervised Pretraining. NeurIPS Hao Liu, Tom Zahavy, Volodymyr Mnih, Satinder Singh
2022	J	`jnl`	Palm up: Playing in the Latent Manifold for Unsupervised Pretraining. CoRR Hao Liu, Tom Zahavy, Volodymyr Mnih, Satinder Singh
2021	J	`jnl`	Discovering Diverse Nearly Optimal Policies withSuccessor Features. CoRR Tom Zahavy, Brendan O'Donoghue, André Barreto, Volodymyr Mnih, Sebastian Flennerhag, Satinder Singh
2021	A*	`conf`	Entropic Desired Dynamics for Intrinsic Control. NeurIPS Steven Hansen, Guillaume Desjardins, Kate Baumli, David Warde-Farley, Nicolas Heess, Simon Osindero, Volodymyr Mnih
2021	A*	`conf`	Relative Variational Intrinsic Control. AAAI Kate Baumli, David Warde-Farley, Steven Hansen, Volodymyr Mnih
2021	J	`jnl`	Wasserstein Distance Maximizing Intrinsic Control. CoRR Ishan Durugkar, Steven Hansen, Stephen Spencer, Volodymyr Mnih
2020	A*	`conf`	Fast Task Inference with Variational Intrinsic Successor Features. ICLR Steven Hansen, Will Dabney, André Barreto, David Warde-Farley, Tom Van de Wiele, Volodymyr Mnih
2020	J	`jnl`	Q-Learning in enormous action spaces via amortized approximate maximization. CoRR Tom Van de Wiele, David Warde-Farley, Andriy Mnih, Volodymyr Mnih
2020	J	`jnl`	Relative Variational Intrinsic Control. CoRR Kate Baumli, David Warde-Farley, Steven Hansen, Volodymyr Mnih
2019	J	`jnl`	Fast Task Inference with Variational Intrinsic Successor Features. CoRR Steven Hansen, Will Dabney, André Barreto, Tom Van de Wiele, David Warde-Farley, Volodymyr Mnih
2019	—	`conf`	Unsupervised Control Through Non-Parametric Discriminative Rewards. ICLR (Poster) David Warde-Farley, Tom Van de Wiele, Tejas D. Kulkarni, Catalin Ionescu, Steven Hansen, Volodymyr Mnih
2019	A*	`conf`	Unsupervised Learning of Object Keypoints for Perception and Control. NeurIPS Tejas D. Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih
2019	J	`jnl`	Unsupervised Learning of Object Keypoints for Perception and Control. CoRR Tejas D. Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih
2018	A*	`conf`	IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures. ICML Lasse Espeholt, Hubert Soyer, Rémi Munos, Karen Simonyan, Volodymyr Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, Shane Legg, Koray Kavukcuoglu
2018	J	`jnl`	IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures. CoRR Lasse Espeholt, Hubert Soyer, Rémi Munos, Karen Simonyan, Volodymyr Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, Shane Legg, Koray Kavukcuoglu
2018	J	`jnl`	Learning by Playing - Solving Sparse Reward Tasks from Scratch. CoRR Martin A. Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom Van de Wiele, Volodymyr Mnih, Nicolas Heess, Jost Tobias Springenberg
2018	—	`conf`	Noisy Networks For Exploration. ICLR (Poster) 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
2018	A*	`conf`	The Uncertainty Bellman Equation and Exploration. ICML Brendan O'Donoghue, Ian Osband, Rémi Munos, Volodymyr Mnih
2018	J	`jnl`	Unsupervised Control Through Non-Parametric Discriminative Rewards. CoRR David Warde-Farley, Tom Van de Wiele, Tejas D. Kulkarni, Catalin Ionescu, Steven Hansen, Volodymyr Mnih
2017	—	`conf`	Combining policy gradient and Q-learning. ICLR (Poster) Brendan O'Donoghue, Rémi Munos, Koray Kavukcuoglu, Volodymyr Mnih
2017	—	`conf`	Reinforcement Learning with Unsupervised Auxiliary Tasks. ICLR Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, Koray Kavukcuoglu
2017	—	`conf`	Sample Efficient Actor-Critic with Experience Replay. ICLR (Poster) Ziyu Wang, Victor Bapst, Nicolas Heess, Volodymyr Mnih, Rémi Munos, Koray Kavukcuoglu, Nando de Freitas
2017	J	`jnl`	The Uncertainty Bellman Equation and Exploration. CoRR Brendan O'Donoghue, Ian Osband, Rémi Munos, Volodymyr Mnih
2016	A*	`conf`	Asynchronous Methods for Deep Reinforcement Learning. ICML Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu
2016	J	`jnl`	Asynchronous Methods for Deep Reinforcement Learning. CoRR Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu
2016	—	`conf`	Learning values across many orders of magnitude. NIPS Hado van Hasselt, Arthur Guez, Matteo Hessel, Volodymyr Mnih, David Silver
2016	J	`jnl`	PGQ: Combining policy gradient and Q-learning. CoRR Brendan O'Donoghue, Rémi Munos, Koray Kavukcuoglu, Volodymyr Mnih
2016	A*	`conf`	Policy Distillation. ICLR (Poster) Andrei A. Rusu, Sergio Gomez Colmenarejo, Çaglar Gülçehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, Raia Hadsell
2016	J	`jnl`	Reinforcement Learning with Unsupervised Auxiliary Tasks. CoRR Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, Koray Kavukcuoglu
2016	J	`jnl`	Sample Efficient Actor-Critic with Experience Replay. CoRR Ziyu Wang, Victor Bapst, Nicolas Heess, Volodymyr Mnih, Rémi Munos, Koray Kavukcuoglu, Nando de Freitas
2016	—	`conf`	Strategic Attentive Writer for Learning Macro-Actions. NIPS Alexander Vezhnevets, Volodymyr Mnih, Simon Osindero, Alex Graves, Oriol Vinyals, John P. Agapiou, Koray Kavukcuoglu
2016	J	`jnl`	Strategic Attentive Writer for Learning Macro-Actions. CoRR Alexander Vezhnevets, Volodymyr Mnih, John P. Agapiou, Simon Osindero, Alex Graves, Oriol Vinyals, Koray Kavukcuoglu
2016	—	`conf`	Using Fast Weights to Attend to the Recent Past. NIPS Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu
2016	J	`jnl`	Using Fast Weights to Attend to the Recent Past. CoRR Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu
2015	J	`jnl`	Human-level control through deep reinforcement learning. Nat. 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
2015	J	`jnl`	Massively Parallel Methods for Deep Reinforcement Learning. CoRR 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
2015	—	`conf`	Multiple Object Recognition with Visual Attention. ICLR (Poster) Jimmy Ba, Volodymyr Mnih, Koray Kavukcuoglu
2014	—	`conf`	Recurrent Models of Visual Attention. NIPS Volodymyr Mnih, Nicolas Heess, Alex Graves, Koray Kavukcuoglu
2014	J	`jnl`	Recurrent Models of Visual Attention. CoRR Volodymyr Mnih, Nicolas Heess, Alex Graves, Koray Kavukcuoglu
2013	—	`—`	Machine Learning for Aerial Image Labeling. Volodymyr Mnih
2013	J	`jnl`	Modeling Natural Images Using Gated MRFs. IEEE Trans. Pattern Anal. Mach. Intell. Marc'Aurelio Ranzato, Volodymyr Mnih, Joshua M. Susskind, Geoffrey E. Hinton
2013	J	`jnl`	Playing Atari with Deep Reinforcement Learning. CoRR Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, Martin A. Riedmiller
2012	J	`jnl`	Conditional Restricted Boltzmann Machines for Structured Output Prediction CoRR Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton
2012	A*	`conf`	Learning to Label Aerial Images from Noisy Data. ICML Volodymyr Mnih, Geoffrey E. Hinton
2011	A	`conf`	Conditional Restricted Boltzmann Machines for Structured Output Prediction. UAI Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton
2011	A*	`conf`	On deep generative models with applications to recognition. CVPR Marc'Aurelio Ranzato, Joshua M. Susskind, Volodymyr Mnih, Geoffrey E. Hinton
2010	—	`conf`	Generating more realistic images using gated MRF's. NIPS Marc'Aurelio Ranzato, Volodymyr Mnih, Geoffrey E. Hinton
2010	—	`conf`	Learning to Detect Roads in High-Resolution Aerial Images. ECCV (6) Volodymyr Mnih, Geoffrey E. Hinton
2008	A*	`conf`	Empirical Bernstein stopping. ICML Volodymyr Mnih, Csaba Szepesvári, Jean-Yves Audibert
2006	J	`jnl`	Topological map learning from outdoor image sequences. J. Field Robotics Xuming He, Richard S. Zemel, Volodymyr Mnih