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Top-KAST: Top-K Always Sparse Training


Jun 07, 2021
Siddhant M. Jayakumar, Razvan Pascanu, Jack W. Rae, Simon Osindero, Erich Elsen

* Advances in Neural Information Processing Systems, 33, 20744-20754 

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A study on the plasticity of neural networks


May 31, 2021
Tudor Berariu, Wojciech Czarnecki, Soham De, Jorg Bornschein, Samuel Smith, Razvan Pascanu, Claudia Clopath


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Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error


May 27, 2021
Stanislav Fort, Andrew Brock, Razvan Pascanu, Soham De, Samuel L. Smith


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Continual World: A Robotic Benchmark For Continual Reinforcement Learning


May 23, 2021
Maciej Wołczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś


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Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective


May 11, 2021
Florin Gogianu, Tudor Berariu, Mihaela Rosca, Claudia Clopath, Lucian Busoniu, Razvan Pascanu

* Accepted at ICML2021 

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Regularized Behavior Value Estimation


Mar 17, 2021
Caglar Gulcehre, Sergio Gómez Colmenarejo, Ziyu Wang, Jakub Sygnowski, Thomas Paine, Konrad Zolna, Yutian Chen, Matthew Hoffman, Razvan Pascanu, Nando de Freitas


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Behavior Priors for Efficient Reinforcement Learning


Oct 27, 2020
Dhruva Tirumala, Alexandre Galashov, Hyeonwoo Noh, Leonard Hasenclever, Razvan Pascanu, Jonathan Schwarz, Guillaume Desjardins, Wojciech Marian Czarnecki, Arun Ahuja, Yee Whye Teh, Nicolas Heess

* Submitted to Journal of Machine Learning Research (JMLR) 

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BYOL works even without batch statistics


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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