Eslami, S. M. Ali

18 publications

NeurIPS 2023 Self-Supervised Video Pretraining Yields Robust and More Human-Aligned Visual Representations Nikhil Parthasarathy, S. M. Ali Eslami, Joao Carreira, Olivier Henaff

ICML 2022 From Data to Functa: Your Data Point Is a Function and You Can Treat It like One Emilien Dupont, Hyunjik Kim, S. M. Ali Eslami, Danilo Jimenez Rezende, Dan Rosenbaum

JAIR 2021 Game Plan: What AI Can Do for Football, and What Football Can Do for AI Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome T. Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adrià Recasens, Alexandre Galashov, Gregory Thornton, Romuald Elie, Pablo Sprechmann, Pol Moreno, Kris Cao, Marta Garnelo, Praneet Dutta, Michal Valko, Nicolas Heess, Alex Bridgland, Julien Pérolat, Bart De Vylder, S. M. Ali Eslami, Mark Rowland, Andrew Jaegle, Rémi Munos, Trevor Back, Razia Ahamed, Simon Bouton, Nathalie Beauguerlange, Jackson Broshear, Thore Graepel, Demis Hassabis

NeurIPS 2021 Multimodal Few-Shot Learning with Frozen Language Models Maria Tsimpoukelli, Jacob L Menick, Serkan Cabi, S. M. Ali Eslami, Oriol Vinyals, Felix Hill

CoRL 2021 Towards Real Robot Learning in the Wild: A Case Study in Bipedal Locomotion Michael Bloesch, Jan Humplik, Viorica Patraucean, Roland Hafner, Tuomas Haarnoja, Arunkumar Byravan, Noah Yamamoto Siegel, Saran Tunyasuvunakool, Federico Casarini, Nathan Batchelor, Francesco Romano, Stefano Saliceti, Martin Riedmiller, S. M. Ali Eslami, Nicolas Heess

ICML 2020 PolyGen: An Autoregressive Generative Model of 3D Meshes Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter Battaglia

NeurIPS 2018 A Probabilistic U-Net for Segmentation of Ambiguous Images Simon Kohl, Bernardino Romera-Paredes, Clemens Meyer, Jeffrey De Fauw, Joseph R. Ledsam, Klaus Maier-Hein, S. M. Ali Eslami, Danilo Jimenez Rezende, Olaf Ronneberger

ICML 2018 Conditional Neural Processes Marta Garnelo, Dan Rosenbaum, Christopher Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo Rezende, S. M. Ali Eslami

ICLR 2018 Few-Shot Autoregressive Density Estimation: Towards Learning to Learn Distributions Scott Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo Rezende, Oriol Vinyals, Nando de Freitas

ICML 2018 Generative Temporal Models with Spatial Memory for Partially Observed Environments Marco Fraccaro, Danilo Rezende, Yori Zwols, Alexander Pritzel, S. M. Ali Eslami, Fabio Viola

ICML 2018 Machine Theory of Mind Neil Rabinowitz, Frank Perbet, Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew Botvinick

ICML 2018 Synthesizing Programs for Images Using Reinforced Adversarial Learning Yaroslav Ganin, Tejas Kulkarni, Igor Babuschkin, S. M. Ali Eslami, Oriol Vinyals

NeurIPS 2016 Attend, Infer, Repeat: Fast Scene Understanding with Generative Models S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Koray Kavukcuoglu, Geoffrey E. Hinton

NeurIPS 2016 Unsupervised Learning of 3D Structure from Images Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter Battaglia, Max Jaderberg, Nicolas Heess

AISTATS 2015 Consensus Message Passing for Layered Graphical Models Varun Jampani, S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John M. Winn

UAI 2015 Kernel-Based Just-in-Time Learning for Passing Expectation Propagation Messages Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltán Szabó

NeurIPS 2014 Just-in-Time Learning for Fast and Flexible Inference S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John Winn

CVPR 2012 The Shape Boltzmann Machine: A Strong Model of Object Shape S. M. Ali Eslami, Nicolas Heess, John M. Winn