Mnih, Volodymyr

33 publications

ICLR 2025 ElasticTok: Adaptive Tokenization for Image and Video Wilson Yan, Volodymyr Mnih, Aleksandra Faust, Matei Zaharia, Pieter Abbeel, Hao Liu

ICML 2025 LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations Anian Ruoss, Fabio Pardo, Harris Chan, Bonnie Li, Volodymyr Mnih, Tim Genewein

ICLRW 2025 LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations Anian Ruoss, Fabio Pardo, Harris Chan, Bonnie Li, Volodymyr Mnih, Tim Genewein

ICLR 2023 In-Context Reinforcement Learning with Algorithm Distillation 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

NeurIPSW 2023 Vision-Language Models as a Source of Rewards Kate Baumli, Satinder Singh, Feryal Behbahani, Harris Chan, Gheorghe Comanici, Sebastian Flennerhag, Maxime Gazeau, Kristian Holsheimer, Dan Horgan, Michael Laskin, Clare Lyle, 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 M Zhang

NeurIPSW 2022 In-Context Reinforcement Learning with Algorithm Distillation 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

NeurIPSW 2022 In-Context Reinforcement Learning with Algorithm Distillation 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

ICLR 2022 Learning More Skills Through Optimistic Exploration Dj Strouse, Kate Baumli, David Warde-Farley, Volodymyr Mnih, Steven Stenberg Hansen

NeurIPS 2022 PaLM up: Playing in the Latent Manifold for Unsupervised Pretraining Hao Liu, Tom Zahavy, Volodymyr Mnih, Satinder P. Singh

ICMLW 2021 Discovering Diverse Nearly Optimal Policies with Successor Features Tom Zahavy, Brendan O'Donoghue, Andre Barreto, Sebastian Flennerhag, Volodymyr Mnih, Satinder Singh

NeurIPS 2021 Entropic Desired Dynamics for Intrinsic Control Steven Hansen, Guillaume Desjardins, Kate Baumli, David Warde-Farley, Nicolas Heess, Simon Osindero, Volodymyr Mnih

AAAI 2021 Relative Variational Intrinsic Control Kate Baumli, David Warde-Farley, Steven Hansen, Volodymyr Mnih

NeurIPSW 2021 Wasserstein Distance Maximizing Intrinsic Control Ishan Durugkar, Steven Stenberg Hansen, Stephen Spencer, Volodymyr Mnih

ICLR 2020 Fast Task Inference with Variational Intrinsic Successor Features Steven Hansen, Will Dabney, Andre Barreto, Tom Van de Wiele, David Warde-Farley, Volodymyr Mnih

ICLR 2019 Unsupervised Control Through Non-Parametric Discriminative Rewards David Warde-Farley, Tom Van de Wiele, Tejas Kulkarni, Catalin Ionescu, Steven Hansen, Volodymyr Mnih

NeurIPS 2019 Unsupervised Learning of Object Keypoints for Perception and Control Tejas D Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih

ICLR 2018 Noisy Networks for Exploration Meire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot, Jacob Menick, Matteo Hessel, Ian Osband, Alex Graves, Volodymyr Mnih, Remi Munos, Demis Hassabis, Olivier Pietquin, Charles Blundell, Shane Legg

ICLR 2017 Combining Policy Gradient and Q-Learning Brendan O'Donoghue, Rémi Munos, Koray Kavukcuoglu, Volodymyr Mnih

ICLR 2017 Reinforcement Learning with Unsupervised Auxiliary Tasks Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, Koray Kavukcuoglu

ICLR 2017 Sample Efficient Actor-Critic with Experience Replay Ziyu Wang, Victor Bapst, Nicolas Heess, Volodymyr Mnih, Rémi Munos, Koray Kavukcuoglu, Nando de Freitas

ICML 2016 Asynchronous Methods for Deep Reinforcement Learning Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu

NeurIPS 2016 Learning Values Across Many Orders of Magnitude Hado P van Hasselt, Arthur Guez, Arthur Guez, Matteo Hessel, Volodymyr Mnih, David Silver

ICLR 2016 Policy Distillation Andrei A. Rusu, Sergio Gomez Colmenarejo, Çaglar Gülçehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, Raia Hadsell

NeurIPS 2016 Strategic Attentive Writer for Learning Macro-Actions Alexander Vezhnevets, Volodymyr Mnih, Simon Osindero, Alex Graves, Oriol Vinyals, John Agapiou, Koray Kavukcuoglu

NeurIPS 2016 Using Fast Weights to Attend to the Recent past Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu

ICLR 2015 Multiple Object Recognition with Visual Attention Jimmy Ba, Volodymyr Mnih, Koray Kavukcuoglu

NeurIPS 2014 Recurrent Models of Visual Attention Volodymyr Mnih, Nicolas Heess, Alex Graves, Koray Kavukcuoglu

ICML 2012 Learning to Label Aerial Images from Noisy Data Volodymyr Mnih, Geoffrey E. Hinton

UAI 2011 Conditional Restricted Boltzmann Machines for Structured Output Prediction Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton

CVPR 2011 On Deep Generative Models with Applications to Recognition Marc'Aurelio Ranzato, Joshua M. Susskind, Volodymyr Mnih, Geoffrey E. Hinton

NeurIPS 2010 Generating More Realistic Images Using Gated MRF's Marc'aurelio Ranzato, Volodymyr Mnih, Geoffrey E. Hinton

ECCV 2010 Learning to Detect Roads in High-Resolution Aerial Images Volodymyr Mnih, Geoffrey E. Hinton

ICML 2008 Empirical Bernstein Stopping Volodymyr Mnih, Csaba Szepesvári, Jean-Yves Audibert