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Muesli: Combining Improvements in Policy Optimization


Apr 13, 2021
Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt


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Causally Correct Partial Models for Reinforcement Learning


Feb 07, 2020
Danilo J. Rezende, Ivo Danihelka, George Papamakarios, Nan Rosemary Ke, Ray Jiang, Theophane Weber, Karol Gregor, Hamza Merzic, Fabio Viola, Jane Wang, Jovana Mitrovic, Frederic Besse, Ioannis Antonoglou, Lars Buesing


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OpenSpiel: A Framework for Reinforcement Learning in Games


Oct 10, 2019
Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinicius Zambaldi, Satyaki Upadhyay, Julien Pérolat, Sriram Srinivasan, Finbarr Timbers, Karl Tuyls, Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Paul Muller, Timo Ewalds, Ryan Faulkner, János Kramár, Bart De Vylder, Brennan Saeta, James Bradbury, David Ding, Sebastian Borgeaud, Matthew Lai, Julian Schrittwieser, Thomas Anthony, Edward Hughes, Ivo Danihelka, Jonah Ryan-Davis


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The Cramer Distance as a Solution to Biased Wasserstein Gradients


May 30, 2017
Marc G. Bellemare, Ivo Danihelka, Will Dabney, Shakir Mohamed, Balaji Lakshminarayanan, Stephan Hoyer, Rémi Munos


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Comparison of Maximum Likelihood and GAN-based training of Real NVPs


May 15, 2017
Ivo Danihelka, Balaji Lakshminarayanan, Benigno Uria, Daan Wierstra, Peter Dayan


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Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes


Oct 27, 2016
Jack W Rae, Jonathan J Hunt, Tim Harley, Ivo Danihelka, Andrew Senior, Greg Wayne, Alex Graves, Timothy P Lillicrap

* in 30th Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain 

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Video Pixel Networks


Oct 03, 2016
Nal Kalchbrenner, Aaron van den Oord, Karen Simonyan, Ivo Danihelka, Oriol Vinyals, Alex Graves, Koray Kavukcuoglu

* 16 pages 

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Memory-Efficient Backpropagation Through Time


Jun 10, 2016
Audrūnas Gruslys, Remi Munos, Ivo Danihelka, Marc Lanctot, Alex Graves


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