Volodymyr Mnih

发表

Human-level control through deep reinforcement learning

Shane Legg, Alex Graves, Marc G. Bellemare, 2015, Nature.

Learning by Playing - Solving Sparse Reward Tasks from Scratch

Martin A. Riedmiller, Thomas Lampe, Jost Tobias Springenberg, 2018, ICML.

Sample Efficient Actor-Critic with Experience Replay pdf

Nando de Freitas, Rémi Munos, Koray Kavukcuoglu, 2016, ICLR.

Playing Atari with Deep Reinforcement Learning pdf

Alex Graves, Koray Kavukcuoglu, Martin A. Riedmiller, 2013, ArXiv.

Asynchronous Methods for Deep Reinforcement Learning pdf

Alex Graves, Koray Kavukcuoglu, David Silver, 2016, ICML.

Efficient Stopping Rules

Csaba Szepesvari, Dale Schuurmans, Volodymyr Mnih, 2008 .

Generating more realistic images using gated MRF's

Geoffrey E. Hinton, Marc'Aurelio Ranzato, Volodymyr Mnih, 2010, NIPS.

Machine Learning for Aerial Image Labeling

Geoffrey E. Hinton, Volodymyr Mnih, Volodymyr Mnih, 2013 .

Policy Distillation pdf

Razvan Pascanu, Sergio Gomez Colmenarejo, Raia Hadsell, 2015, ICLR.

Learning to Detect Roads in High-Resolution Aerial Images

Geoffrey E. Hinton, Volodymyr Mnih, Volodymyr Mnih, 2010, ECCV.

CUDAMat: a CUDA-based matrix class for Python

Volodymyr Mnih, Volodymyr Mnih, 2009 .

Massively Parallel Methods for Deep Reinforcement Learning pdf

Shane Legg, Praveen Srinivasan, Koray Kavukcuoglu, 2015, ArXiv.

Recurrent Models of Visual Attention

Alex Graves, Koray Kavukcuoglu, Nicolas Heess, 2014, NIPS.

Learning values across many orders of magnitude

David Silver, Matteo Hessel, Arthur Guez, 2016, NIPS.

Using Fast Weights to Attend to the Recent Past

Geoffrey E. Hinton, Joel Z. Leibo, Jimmy Ba, 2016, NIPS.

Combining policy gradient and Q-learning

Koray Kavukcuoglu, Brendan O'Donoghue, Volodymyr Mnih, 2016, ICLR.

Unsupervised Control Through Non-Parametric Discriminative Rewards pdf

David Warde-Farley, Volodymyr Mnih, Tejas D. Kulkarni, 2018, ICLR.

How to generate realistic images using gated MRF ’ s

Geoffrey E. Hinton, Marc'Aurelio Ranzato, Volodymyr Mnih, 2010 .

PGQ: Combining policy gradient and Q-learning pdf

Koray Kavukcuoglu, Brendan O'Donoghue, Volodymyr Mnih, 2016, ArXiv.

Modeling Natural Images Using Gated MRFs

Geoffrey E. Hinton, Marc'Aurelio Ranzato, Volodymyr Mnih, 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

On deep generative models with applications to recognition

Geoffrey E. Hinton, Marc'Aurelio Ranzato, Volodymyr Mnih, 2011, CVPR 2011.

Empirical Bernstein stopping

Csaba Szepesvári, Volodymyr Mnih, Jean-Yves Audibert, 2008, ICML '08.

Learning to Label Aerial Images from Noisy Data

Geoffrey E. Hinton, Volodymyr Mnih, Volodymyr Mnih, 2012, ICML.

Unsupervised Learning of Object Keypoints for Perception and Control

Ankush Gupta, Andrew Zisserman, Volodymyr Mnih, 2019, NeurIPS.

Topological map learning from outdoor image sequences

Richard S. Zemel, Xuming He, Volodymyr Mnih, 2006, J. Field Robotics.

Entropic Desired Dynamics for Intrinsic Control

N. Heess, Volodymyr Mnih, Simon Osindero, 2021, NeurIPS.

Unsupervised Control Through Non-Parametric Discriminative Rewards

Tejas D. Kulkarni, Volodymyr Mnih, T. Wiele, 2018, ICLR.

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures pdf

Shane Legg, Rémi Munos, Iain Dunning, 2018, ICML.

VISUAL ATTENTION

Jimmy Ba, K. Kavukcuoglu, Volodymyr Mnih, 2015 .

Hoeffding Bounds vs . Empirical

Csaba Szepesvari, Volodymyr Mnih, 2018 .

In-context Reinforcement Learning with Algorithm Distillation

Junhyuk Oh, Satinder Singh, Ethan A. Brooks, 2022, ICLR.

Palm up: Playing in the Latent Manifold for Unsupervised Pretraining

Volodymyr Mnih, Satinder Singh, Hao Liu, 2022, NeurIPS.

Relative Variational Intrinsic Control

David Warde-Farley, Volodymyr Mnih, Kate Baumli, 2020, AAAI.

The Uncertainty Bellman Equation and Exploration

Ian Osband, Brendan O'Donoghue, Volodymyr Mnih, 2017, ICML.

Reinforcement Learning with Unsupervised Auxiliary Tasks pdf

Tom Schaul, Joel Z. Leibo, Max Jaderberg, 2016, ICLR.

Multiple Object Recognition with Visual Attention pdf

Koray Kavukcuoglu, Jimmy Ba, Volodymyr Mnih, 2014, ICLR.

Fast Task Inference with Variational Intrinsic Successor Features pdf

David Warde-Farley, Volodymyr Mnih, André Barreto, 2019, ICLR.

Q-Learning in enormous action spaces via amortized approximate maximization pdf

Andriy Mnih, David Warde-Farley, Volodymyr Mnih, 2020, ArXiv.

Strategic Attentive Writer for Learning Macro-Actions

Alex Graves, Simon Osindero, Koray Kavukcuoglu, 2016, NIPS.

Conditional Restricted Boltzmann Machines for Structured Output Prediction

Geoffrey E. Hinton, Hugo Larochelle, Volodymyr Mnih, 2011, UAI.

Wasserstein Distance Maximizing Intrinsic Control pdf

Ishan Durugkar, Volodymyr Mnih, Steven Hansen, 2021, ArXiv.

Discovering Diverse Nearly Optimal Policies withSuccessor Features pdf

Brendan O'Donoghue, Tom Zahavy, Volodymyr Mnih, 2021, ArXiv.

Human-level control through deep reinforcement learning

Marc G. Bellemare, Martin A. Riedmiller, Andrei A. Rusu, 2015, Nature.

Modeling Natural Images Using Gated MRFs

Geoffrey E. Hinton, Marc'Aurelio Ranzato, Volodymyr Mnih, 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Vision-Language Models as a Source of Rewards

Feryal M. P. Behbahani, Dan Horgan, T. Schaul, 2023, 2312.09187.

Visual Attention

Jeremy M Wolfe, Todd S Horowitz, Ester Reijnen, 2020, Computational Models for Cognitive Vision.