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ipie: A Python-based Auxiliary-Field Quantum Monte Carlo Program with Flexibility and Efficiency on CPUs and GPUs

Fionn Malone *, Ankit Mahajan *, James Spencer, Joonho Lee *

Journal of Chemical Theory and Computation

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Sideways: Depth-Parallel Training of Video Models

Mateusz Malinowski, Grzegorz Swirszcz, Joao Carreira, Viorica Patraucean

arXiv

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The StreetLearn Environment and Dataset

Piotr Mirowski, András György, Keith Anderson, Denis Teplyashin, Karl Moritz Hermann, Mateusz Malinowski, Matthew Grimes, Karen Simonyan, Koray Kavukcuoglu, Andrew Zisserman, Raia Hadsell

arXiv

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TF-Replicator: Distributed Machine Learning for Researchers

Peter Buchlovsky, David Budden, Dominik Grewe, Chris Jones, Frederic Besse, Andrew Brock, Aidan Clark, Sergio Colmenarejo *, Aedan Pope, Fabio Viola, Dan Belov, John Aslanides

arXiv

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Learning to Navigate in Cities Without a Map

Piotr Mirowski, Matthew Grimes, Mateusz Malinowski, Karl Moritz Hermann, Keith Anderson, Denis Teplyashin, Karen Simonyan, Koray Kavukcuoglu, Andrew Zisserman, Raia Hadsell

NeurIPS

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Learning Deployable Navigation Policies at Kilometer Scale from a Single Traversal

Jake Bruce, Niko Sünderhauf *, Piotr Mirowski, Raia Hadsell, Michael Milford *

CoRL

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IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

Lasse Espeholt, Hubert Soyer, Rémi Munos, Karen Simonyan, Vlad Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, Shane Legg, Koray Kavukcuoglu

arXiv

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Massively Parallel Methods for Deep Reinforcement Learning

Arun Nair, Prav Srinivasan, Sam Blackwell, Cagdas Alcicek, Rory Fearon, Alessandro De Maria, Veda Panneershelvam, Mustafa Suleyman, Charlie Beattie, Stig Petersen, Shane Legg, Vlad Mnih, Koray Kavukcuoglu, David Silver

ICML

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