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Deep Audio-Visual Speech Recognition

Triantafyllos Afouras *, J S Chung *, Andrew Senior, Oriol Vinyals, Andrew Zisserman

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Representation Learning with Contrastive Predictive Coding

Aäron van den Oord, Yazhe Li, Oriol Vinyals

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The challenge of realistic music generation: modelling raw audio at scale

Sander Dieleman, Aäron van den Oord, Karen Simonyan

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Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures

Timothy Lillicrap, S Bartunov, Adam Santoro, B A Richards *, Geoff Hinton *

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A Probabilistic U-Net for Segmentation of Ambiguous Images

Simon A. A. Kohl, Bernadino Romera Paredes, Clemens Meyer, Jeffrey De Fauw, Joseph Ledsam, Klaus H Maier-Hein *, S M Ali Eslami, Danilo Jimenez Rezende, Olaf Ronneberger

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Playing hard exploration games by watching YouTube

Yusuf Aytar, Tobias Pfaff, David Budden, Tom Le Paine, Ziyu Wang, Nando de Freitas

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Implicit Reparameterization Gradients

Michael Figurnov, Shakir Mohamed, Andriy Mnih

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Neural Discrete Representation Learning

Aäron van den Oord, Oriol Vinyals, Koray Kavukcuoglu

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A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning

Marc Lanctot, Vinicius Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Perolat, David Silver, Thore Graepel

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Variational Memory Addressing in Generative Models

Jörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo Jimenez Rezende

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A multi-agent reinforcement learning model of common-pool resource appropriation

Julien Perolat, Joel Leibo, Vinicius Zambaldi, Charlie Beattie, Karl Tuyls, Thore Graepel

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Imagination-Augmented Agents for Deep Reinforcement Learning

Theophane Weber, Sébastien Racanière, David Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech, Oriol Vinyals, Nicolas Heess, Yazhe Li, Razvan Pascanu, Peter Battaglia, David Silver, Daan Wierstra

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Robust Imitation of Diverse Behaviors

Ziyu Wang, Josh Merel, Scott Reed, Gregory Wayne, Nando de Freitas, Nicolas Heess

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Distral: Robust Multitask Reinforcement Learning

Yee Whye Teh, Victor Bapst, Wojciech Marian Czarnecki, John Quan, James Kirkpatrick, Raia Hadsell, Nicolas Heess, Razvan Pascanu

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Sobolev Training for Neural Networks

Wojciech Marian Czarnecki, Simon Osindero, Max Jaderberg, Grzegorz Swirszcz, Razvan Pascanu

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Deep reinforcement learning from human preferences

Paul Christiano *, Jan Leike, Tom Brown *, Miljan Martic, Shane Legg, Dario Amodei *

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Visual Interaction Networks

Nick Watters, Andrea Tacchetti, Theophane Weber, Razvan Pascanu, Peter Battaglia, Daniel Zoran

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A simple neural network module for relational reasoning

Adam Santoro, David Raposo, David Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, Timothy Lillicrap

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Filtering Variational Objectives

Christopher Maddison, D Lawson *, George Tucker *, Nicolas Heess, Mohammad Norouzi *, Andriy Mnih, Arnaud Doucet, Yee Whye Teh

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Natural Value Approximators: Learning when to Trust Past Estimates

Zhongwen Xu, Joseph Modayil, Hado van Hasselt, André Barreto, David Silver, Tom Schaul

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Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

Balaji Lakshminarayanan, Alexander Pritzel, Charles Blundell

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Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes

Jack Rae, Jonathan Hunt, Tim Harley, Ivo Danihelka, Andrew Senior, Gregory Wayne, Alexander Graves, Timothy Lillicrap

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Unsupervised Learning of 3D Structure from Images

Danilo Jimenez Rezende, S M Ali Eslami, Shakir Mohamed, Peter Battaglia, Max Jaderberg, Nicolas Heess

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Attend, Infer, Repeat: Fast Scene Understanding with Generative Models

S M Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvpari, Koray Kavukcuoglu, Geoff Hinton *

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Strategic Attentive Writer for Learning Macro-Actions

Alexander Vezhnevets, Vlad Mnih, John Agapiou, Simon Osindero, Alexander Graves, Oriol Vinyals, Koray Kavukcuoglu

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