Volodymyr Mnih

According to our database1, Volodymyr Mnih authored at least 33 papers between 2006 and 2018.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2018
Learning by Playing - Solving Sparse Reward Tasks from Scratch.
CoRR, 2018

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures.
CoRR, 2018

Learning by Playing Solving Sparse Reward Tasks from Scratch.
Proceedings of the 35th International Conference on Machine Learning, 2018

The Uncertainty Bellman Equation and Exploration.
Proceedings of the 35th International Conference on Machine Learning, 2018

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
The Uncertainty Bellman Equation and Exploration.
CoRR, 2017

Noisy Networks for Exploration.
CoRR, 2017

2016
Sample Efficient Actor-Critic with Experience Replay.
CoRR, 2016

Strategic Attentive Writer for Learning Macro-Actions.
CoRR, 2016

PGQ: Combining policy gradient and Q-learning.
CoRR, 2016

Asynchronous Methods for Deep Reinforcement Learning.
CoRR, 2016

Reinforcement Learning with Unsupervised Auxiliary Tasks.
CoRR, 2016

Using Fast Weights to Attend to the Recent Past.
CoRR, 2016

Strategic Attentive Writer for Learning Macro-Actions.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning values across many orders of magnitude.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Using Fast Weights to Attend to the Recent Past.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Asynchronous Methods for Deep Reinforcement Learning.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Human-level control through deep reinforcement learning.
Nature, 2015

Policy Distillation.
CoRR, 2015

Massively Parallel Methods for Deep Reinforcement Learning.
CoRR, 2015

2014
Recurrent Models of Visual Attention.
CoRR, 2014

Multiple Object Recognition with Visual Attention.
CoRR, 2014

Recurrent Models of Visual Attention.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Modeling Natural Images Using Gated MRFs.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

Playing Atari with Deep Reinforcement Learning.
CoRR, 2013

2012
Conditional Restricted Boltzmann Machines for Structured Output Prediction
CoRR, 2012

Learning to Label Aerial Images from Noisy Data.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Conditional Restricted Boltzmann Machines for Structured Output Prediction.
Proceedings of the UAI 2011, 2011

On deep generative models with applications to recognition.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010
Generating more realistic images using gated MRF's.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Learning to Detect Roads in High-Resolution Aerial Images.
Proceedings of the Computer Vision - ECCV 2010, 2010

2008
Empirical Bernstein stopping.
Proceedings of the Machine Learning, 2008

2006
Topological map learning from outdoor image sequences.
J. Field Robotics, 2006


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