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Oct 20, 2020
Pierre H. Richemond, Jean-Bastien Grill, Florent Altché, Corentin Tallec, Florian Strub, Andrew Brock, Samuel Smith, Soham De, Razvan Pascanu, Bilal Piot, Michal Valko


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Linear Mode Connectivity in Multitask and Continual Learning

Oct 09, 2020
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Dilan Gorur, Razvan Pascanu, Hassan Ghasemzadeh


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Temporal Difference Uncertainties as a Signal for Exploration

Oct 05, 2020
Sebastian Flennerhag, Jane X. Wang, Pablo Sprechmann, Francesco Visin, Alexandre Galashov, Steven Kapturowski, Diana L. Borsa, Nicolas Heess, Andre Barreto, Razvan Pascanu

* 8 pages, 11 figures, 5 tables 

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Understanding the Role of Training Regimes in Continual Learning

Jun 12, 2020
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Razvan Pascanu, Hassan Ghasemzadeh


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Pointer Graph Networks

Jun 11, 2020
Petar Veličković, Lars Buesing, Matthew C. Overlan, Razvan Pascanu, Oriol Vinyals, Charles Blundell


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A Deep Neural Network's Loss Surface Contains Every Low-dimensional Pattern

Jan 02, 2020
Wojciech Marian Czarnecki, Simon Osindero, Razvan Pascanu, Max Jaderberg


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Continual Unsupervised Representation Learning

Oct 31, 2019
Dushyant Rao, Francesco Visin, Andrei A. Rusu, Yee Whye Teh, Razvan Pascanu, Raia Hadsell

* NeurIPS 2019 

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Improving the Gating Mechanism of Recurrent Neural Networks

Oct 22, 2019
Albert Gu, Caglar Gulcehre, Tom Le Paine, Matt Hoffman, Razvan Pascanu


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Stabilizing Transformers for Reinforcement Learning

Oct 13, 2019
Emilio Parisotto, H. Francis Song, Jack W. Rae, Razvan Pascanu, Caglar Gulcehre, Siddhant M. Jayakumar, Max Jaderberg, Raphael Lopez Kaufman, Aidan Clark, Seb Noury, Matthew M. Botvinick, Nicolas Heess, Raia Hadsell


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Meta-Learning with Warped Gradient Descent

Aug 30, 2019
Sebastian Flennerhag, Andrei A. Rusu, Razvan Pascanu, Hujun Yin, Raia Hadsell

* 27 pages, 11 figures, 4 tables 

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Task Agnostic Continual Learning via Meta Learning

Jun 12, 2019
Xu He, Jakub Sygnowski, Alexandre Galashov, Andrei A. Rusu, Yee Whye Teh, Razvan Pascanu


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Meta-learning of Sequential Strategies

May 08, 2019
Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alex Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin Miller, Mohammad Azar, Ian Osband, Neil Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew Botvinick, Shane Legg

* DeepMind Technical Report (15 pages, 6 figures) 

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Information asymmetry in KL-regularized RL

May 03, 2019
Alexandre Galashov, Siddhant M. Jayakumar, Leonard Hasenclever, Dhruva Tirumala, Jonathan Schwarz, Guillaume Desjardins, Wojciech M. Czarnecki, Yee Whye Teh, Razvan Pascanu, Nicolas Heess

* Accepted as a conference paper at ICLR 2019 

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Ray Interference: a Source of Plateaus in Deep Reinforcement Learning

Apr 25, 2019
Tom Schaul, Diana Borsa, Joseph Modayil, Razvan Pascanu

* Full version of RLDM abstract 

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A RAD approach to deep mixture models

Mar 18, 2019
Laurent Dinh, Jascha Sohl-Dickstein, Razvan Pascanu, Hugo Larochelle

* 9 pages of main content, 4 pages of appendices 

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Exploiting Hierarchy for Learning and Transfer in KL-regularized RL

Mar 18, 2019
Dhruva Tirumala, Hyeonwoo Noh, Alexandre Galashov, Leonard Hasenclever, Arun Ahuja, Greg Wayne, Razvan Pascanu, Yee Whye Teh, Nicolas Heess


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Distilling Policy Distillation

Feb 06, 2019
Wojciech Marian Czarnecki, Razvan Pascanu, Simon Osindero, Siddhant M. Jayakumar, Grzegorz Swirszcz, Max Jaderberg

* Accepted at AISTATS 2019 

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Functional Regularisation for Continual Learning using Gaussian Processes

Jan 31, 2019
Michalis K. Titsias, Jonathan Schwarz, Alexander G. de G. Matthews, Razvan Pascanu, Yee Whye Teh


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Adapting Auxiliary Losses Using Gradient Similarity

Dec 05, 2018
Yunshu Du, Wojciech M. Czarnecki, Siddhant M. Jayakumar, Razvan Pascanu, Balaji Lakshminarayanan


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Relational inductive biases, deep learning, and graph networks

Oct 17, 2018
Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Caglar Gulcehre, Francis Song, Andrew Ballard, Justin Gilmer, George Dahl, Ashish Vaswani, Kelsey Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matt Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu


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Meta-Learning with Latent Embedding Optimization

Sep 28, 2018
Andrei A. Rusu, Dushyant Rao, Jakub Sygnowski, Oriol Vinyals, Razvan Pascanu, Simon Osindero, Raia Hadsell


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Block Mean Approximation for Efficient Second Order Optimization

Aug 29, 2018
Yao Lu, Mehrtash Harandi, Richard Hartley, Razvan Pascanu


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Been There, Done That: Meta-Learning with Episodic Recall

Jul 06, 2018
Samuel Ritter, Jane X. Wang, Zeb Kurth-Nelson, Siddhant M. Jayakumar, Charles Blundell, Razvan Pascanu, Matthew Botvinick

* ICML 2018 

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Progress & Compress: A scalable framework for continual learning

Jul 02, 2018
Jonathan Schwarz, Jelena Luketina, Wojciech M. Czarnecki, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, Raia Hadsell

* Accepted at ICML 2018 

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Relational recurrent neural networks

Jun 28, 2018
Adam Santoro, Ryan Faulkner, David Raposo, Jack Rae, Mike Chrzanowski, Theophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, Timothy Lillicrap


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Relational Deep Reinforcement Learning

Jun 28, 2018
Vinicius Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David Reichert, Timothy Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew Botvinick, Oriol Vinyals, Peter Battaglia


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Mix&Match - Agent Curricula for Reinforcement Learning

Jun 05, 2018
Wojciech Marian Czarnecki, Siddhant M. Jayakumar, Max Jaderberg, Leonard Hasenclever, Yee Whye Teh, Simon Osindero, Nicolas Heess, Razvan Pascanu

* ICML 2018 

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Hyperbolic Attention Networks

May 24, 2018
Caglar Gulcehre, Misha Denil, Mateusz Malinowski, Ali Razavi, Razvan Pascanu, Karl Moritz Hermann, Peter Battaglia, Victor Bapst, David Raposo, Adam Santoro, Nando de Freitas


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Sim-to-Real Robot Learning from Pixels with Progressive Nets

May 22, 2018
Andrei A. Rusu, Mel Vecerik, Thomas Rothörl, Nicolas Heess, Razvan Pascanu, Raia Hadsell


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