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Skillful Precipitation Nowcasting using Deep Generative Models of Radar


Apr 02, 2021
Suman Ravuri, Karel Lenc, Matthew Willson, Dmitry Kangin, Remi Lam, Piotr Mirowski, Megan Fitzsimons, Maria Athanassiadou, Sheleem Kashem, Sam Madge, Rachel Prudden, Amol Mandhane, Aidan Clark, Andrew Brock, Karen Simonyan, Raia Hadsell, Niall Robinson, Ellen Clancy, Alberto Arribas, Shakir Mohamed

* 46 pages, 17 figures, 2 tables 

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Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities


Feb 09, 2021
Nenad Tomasev, Kevin R. McKee, Jackie Kay, Shakir Mohamed


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A case for new neural network smoothness constraints


Dec 21, 2020
Mihaela Rosca, Theophane Weber, Arthur Gretton, Shakir Mohamed


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Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence


Jul 08, 2020
Shakir Mohamed, Marie-Therese Png, William Isaac

* 28 Pages. Accepted, to appear in: Philosophy and Technology (405), Springer. Submitted 16 January, Accepted 26 May 2020 

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A review of radar-based nowcasting of precipitation and applicable machine learning techniques


May 11, 2020
Rachel Prudden, Samantha Adams, Dmitry Kangin, Niall Robinson, Suman Ravuri, Shakir Mohamed, Alberto Arribas

* 17 pages This work has been submitted to Monthly Weather Review. Copyright in this work may be transferred without further notice 

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Levels of Analysis for Machine Learning


Apr 06, 2020
Jessica Hamrick, Shakir Mohamed

* Accepted to the workshop on "Bridging AI and Cognitive Science" at ICLR 2020 

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Normalizing Flows for Probabilistic Modeling and Inference


Dec 05, 2019
George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan

* Review article. 60 pages, 4 figures 

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Monte Carlo Gradient Estimation in Machine Learning


Jun 25, 2019
Shakir Mohamed, Mihaela Rosca, Michael Figurnov, Andriy Mnih

* 59 pages, under review 

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Training language GANs from Scratch


May 23, 2019
Cyprien de Masson d'Autume, Mihaela Rosca, Jack Rae, Shakir Mohamed


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Implicit Reparameterization Gradients


Nov 01, 2018
Michael Figurnov, Shakir Mohamed, Andriy Mnih

* NIPS 2018 

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Learning Implicit Generative Models with the Method of Learned Moments


Jun 28, 2018
Suman Ravuri, Shakir Mohamed, Mihaela Rosca, Oriol Vinyals

* ICML 2018, 6 figures, 17 pages 

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Unsupervised Learning of 3D Structure from Images


Jun 19, 2018
Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter Battaglia, Max Jaderberg, Nicolas Heess

* Appears in Advances in Neural Information Processing Systems 29 (NIPS 2016) 

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Distribution Matching in Variational Inference


Jun 12, 2018
Mihaela Rosca, Balaji Lakshminarayanan, Shakir Mohamed


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Unsupervised Predictive Memory in a Goal-Directed Agent


Mar 28, 2018
Greg Wayne, Chia-Chun Hung, David Amos, Mehdi Mirza, Arun Ahuja, Agnieszka Grabska-Barwinska, Jack Rae, Piotr Mirowski, Joel Z. Leibo, Adam Santoro, Mevlana Gemici, Malcolm Reynolds, Tim Harley, Josh Abramson, Shakir Mohamed, Danilo Rezende, David Saxton, Adam Cain, Chloe Hillier, David Silver, Koray Kavukcuoglu, Matt Botvinick, Demis Hassabis, Timothy Lillicrap


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Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step


Feb 20, 2018
William Fedus, Mihaela Rosca, Balaji Lakshminarayanan, Andrew M. Dai, Shakir Mohamed, Ian Goodfellow

* 18 pages 

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Variational Approaches for Auto-Encoding Generative Adversarial Networks


Oct 21, 2017
Mihaela Rosca, Balaji Lakshminarayanan, David Warde-Farley, Shakir Mohamed


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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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Recurrent Environment Simulators


Apr 19, 2017
Silvia Chiappa, Sébastien Racaniere, Daan Wierstra, Shakir Mohamed


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Learning in Implicit Generative Models


Feb 27, 2017
Shakir Mohamed, Balaji Lakshminarayanan


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Generative Temporal Models with Memory


Feb 21, 2017
Mevlana Gemici, Chia-Chun Hung, Adam Santoro, Greg Wayne, Shakir Mohamed, Danilo J. Rezende, David Amos, Timothy Lillicrap


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Normalizing Flows on Riemannian Manifolds


Nov 09, 2016
Mevlana C. Gemici, Danilo Rezende, Shakir Mohamed

* 3 pages, 2 figures, Submitted to Workshop on Bayesian Deep Learning at NIPS 2016 

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Early Visual Concept Learning with Unsupervised Deep Learning


Sep 20, 2016
Irina Higgins, Loic Matthey, Xavier Glorot, Arka Pal, Benigno Uria, Charles Blundell, Shakir Mohamed, Alexander Lerchner


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Expectation Propagation in Gaussian Process Dynamical Systems: Extended Version


Aug 17, 2016
Marc Peter Deisenroth, Shakir Mohamed

* Advances in Neural Information Processing Systems 25 (NIPS), pp. 2609-2617, 2012 

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Variational Inference with Normalizing Flows


Jun 14, 2016
Danilo Jimenez Rezende, Shakir Mohamed

* Proceedings of the 32nd International Conference on Machine Learning 

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One-Shot Generalization in Deep Generative Models


May 25, 2016
Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra

* 8pgs, 1pg references, 1pg appendix, In Proceedings of the 33rd International Conference on Machine Learning, JMLR: W&CP volume 48, 2016 

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Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning


Sep 29, 2015
Shakir Mohamed, Danilo Jimenez Rezende

* Proceedings of the 29th Conference on Neural Information Processing Systems (NIPS 2015) 

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Semi-Supervised Learning with Deep Generative Models


Oct 31, 2014
Diederik P. Kingma, Danilo J. Rezende, Shakir Mohamed, Max Welling

* To appear in the proceedings of Neural Information Processing Systems (NIPS) 2014 

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Stochastic Backpropagation and Approximate Inference in Deep Generative Models


May 30, 2014
Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra

* Appears In Proceedings of the 31st International Conference on Machine Learning (ICML), JMLR: W\&CP volume 32, 2014 

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Bayesian and L1 Approaches to Sparse Unsupervised Learning


Aug 17, 2012
Shakir Mohamed, Katherine Heller, Zoubin Ghahramani

* In Proceedings of the 29th International Conference on Machine Learning (ICML), Edinburgh, Scotland, 2012 

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