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Contrastive Training for Improved Out-of-Distribution Detection

Jul 10, 2020
Jim Winkens, Rudy Bunel, Abhijit Guha Roy, Robert Stanforth, Vivek Natarajan, Joseph R. Ledsam, Patricia MacWilliams, Pushmeet Kohli, Alan Karthikesalingam, Simon Kohl, Taylan Cemgil, S. M. Ali Eslami, Olaf Ronneberger


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PolyGen: An Autoregressive Generative Model of 3D Meshes

Feb 23, 2020
Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter W. Battaglia


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Unsupervised Doodling and Painting with Improved SPIRAL

Oct 02, 2019
John F. J. Mellor, Eunbyung Park, Yaroslav Ganin, Igor Babuschkin, Tejas Kulkarni, Dan Rosenbaum, Andy Ballard, Theophane Weber, Oriol Vinyals, S. M. Ali Eslami

* See https://learning-to-paint.github.io for an interactive version of this paper, with videos 

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A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities

May 30, 2019
Simon A. A. Kohl, Bernardino Romera-Paredes, Klaus H. Maier-Hein, Danilo Jimenez Rezende, S. M. Ali Eslami, Pushmeet Kohli, Andrew Zisserman, Olaf Ronneberger

* 25 pages, 15 figures 

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Data-Efficient Image Recognition with Contrastive Predictive Coding

May 22, 2019
Olivier J. Hénaff, Ali Razavi, Carl Doersch, S. M. Ali Eslami, Aaron van den Oord


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Meta-Learning surrogate models for sequential decision making

Mar 28, 2019
Alexandre Galashov, Jonathan Schwarz, Hyunjik Kim, Marta Garnelo, David Saxton, Pushmeet Kohli, S. M. Ali Eslami, Yee Whye Teh


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A Probabilistic U-Net for Segmentation of Ambiguous Images

Oct 29, 2018
Simon A. A. Kohl, Bernardino Romera-Paredes, Clemens Meyer, Jeffrey De Fauw, Joseph R. Ledsam, Klaus H. Maier-Hein, S. M. Ali Eslami, Danilo Jimenez Rezende, Olaf Ronneberger

* 11 pages for the main paper, 28 pages including appendix. 5 figures in the main paper, 18 figures in total, Advances in Neural Information Processing Systems (NIPS), 2018 

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Consistent Jumpy Predictions for Videos and Scenes

Oct 02, 2018
Ananya Kumar, S. M. Ali Eslami, Danilo J. Rezende, Marta Garnelo, Fabio Viola, Edward Lockhart, Murray Shanahan


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Generative Temporal Models with Spatial Memory for Partially Observed Environments

Jul 19, 2018
Marco Fraccaro, Danilo Jimenez Rezende, Yori Zwols, Alexander Pritzel, S. M. Ali Eslami, Fabio Viola

* ICML 2018 

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Encoding Spatial Relations from Natural Language

Jul 05, 2018
Tiago Ramalho, Tom√°Ň° Końćisk√Ĺ, Frederic Besse, S. M. Ali Eslami, G√°bor Melis, Fabio Viola, Phil Blunsom, Karl Moritz Hermann


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Learning models for visual 3D localization with implicit mapping

Jul 04, 2018
Dan Rosenbaum, Frederic Besse, Fabio Viola, Danilo J. Rezende, S. M. Ali Eslami


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Neural Processes

Jul 04, 2018
Marta Garnelo, Jonathan Schwarz, Dan Rosenbaum, Fabio Viola, Danilo J. Rezende, S. M. Ali Eslami, Yee Whye Teh


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Conditional Neural Processes

Jul 04, 2018
Marta Garnelo, Dan Rosenbaum, Chris J. Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo J. Rezende, S. M. Ali Eslami


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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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Synthesizing Programs for Images using Reinforced Adversarial Learning

Apr 03, 2018
Yaroslav Ganin, Tejas Kulkarni, Igor Babuschkin, S. M. Ali Eslami, Oriol Vinyals

* 12 pages, 13 figures 

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Machine Theory of Mind

Mar 12, 2018
Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew Botvinick

* 21 pages, 15 figures 

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Kickstarting Deep Reinforcement Learning

Mar 10, 2018
Simon Schmitt, Jonathan J. Hudson, Augustin Zidek, Simon Osindero, Carl Doersch, Wojciech M. Czarnecki, Joel Z. Leibo, Heinrich Kuttler, Andrew Zisserman, Karen Simonyan, S. M. Ali Eslami


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Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions

Feb 28, 2018
Scott Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo Rezende, Oriol Vinyals, Nando de Freitas


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Learning and Querying Fast Generative Models for Reinforcement Learning

Feb 08, 2018
Lars Buesing, Theophane Weber, Sebastien Racaniere, S. M. Ali Eslami, Danilo Rezende, David P. Reichert, Fabio Viola, Frederic Besse, Karol Gregor, Demis Hassabis, Daan Wierstra


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Emergence of Locomotion Behaviours in Rich Environments

Jul 10, 2017
Nicolas Heess, Dhruva TB, Srinivasan Sriram, Jay Lemmon, Josh Merel, Greg Wayne, Yuval Tassa, Tom Erez, Ziyu Wang, S. M. Ali Eslami, Martin Riedmiller, David Silver


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

Aug 12, 2016
S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Koray Kavukcuoglu, Geoffrey E. Hinton


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Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages

Jun 09, 2015
Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltán Szabó

* accepted to UAI 2015. Correct typos. Add more content to the appendix. Main results unchanged 

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Consensus Message Passing for Layered Graphical Models

Jan 26, 2015
Varun Jampani, S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John Winn

* Appearing in Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS) 2015 

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