S. M. Ali Eslami

According to our database, S. M. Ali Eslami authored at least 44 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Advancing Multimodal Medical Capabilities of Gemini.

Lin Yang, Shawn Xu, Andrew Sellergren, Timo Kohlberger, Yuchen Zhou, Ira Ktena, Atilla P. Kiraly, Faruk Ahmed, Farhad Hormozdiari, Tiam Jaroensri, Eric Wang, Ellery Wulczyn, Fayaz Jamil, Theo Guidroz, Chuck Lau, Siyuan Qiao, Yun Liu, Akshay Goel, Kendall Park, Arnav Agharwal, Nick George, Yang Wang, Ryutaro Tanno, David G. T. Barrett, Wei-Hung Weng, S. Sara Mahdavi, Khaled Saab, Tao Tu, Sreenivasa Raju Kalidindi, Mozziyar Etemadi, Jorge Cuadros, Gregory Sorensen, Yossi Matias, Katherine Chou, Greg Corrado, Joelle K. Barral, Shravya Shetty, David J. Fleet, S. M. Ali Eslami, Daniel Tse, Shruthi Prabhakara, Cory Y. McLean, Dave Steiner, Rory Pilgrim, Christopher Kelly, Shekoofeh Azizi, Daniel Golden

CoRR, 2024

Capabilities of Gemini Models in Medicine.

Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno, David Stutz, Ellery Wulczyn, Fan Zhang, Tim Strother, Chunjong Park, Elahe Vedadi, Juanma Zambrano Chaves, Szu-Yeu Hu, Mike Schaekermann, Aishwarya Kamath, Yong Cheng, David G. T. Barrett, Cathy Cheung, Basil Mustafa, Anil Palepu, Daniel McDuff, Le Hou, Tomer Golany, Luyang Liu, Jean-Baptiste Alayrac, Neil Houlsby, Nenad Tomasev, Jan Freyberg, Charles Lau, Jonas Kemp, Jeremy Lai, Shekoofeh Azizi, Kimberly Kanada, SiWai Man, Kavita Kulkarni, Ruoxi Sun, Siamak Shakeri, Luheng He, Benjamin Caine, Albert Webson, Natasha Latysheva, Melvin Johnson, Philip Andrew Mansfield, Jian Lu, Ehud Rivlin, Jesper Anderson, Bradley Green, Renee Wong, Jonathan Krause, Jonathon Shlens, Ewa Dominowska, S. M. Ali Eslami, Katherine Chou, Claire Cui, Oriol Vinyals, Koray Kavukcuoglu, James Manyika, Jeff Dean, Demis Hassabis, Yossi Matias, Dale R. Webster, Joelle K. Barral, Greg Corrado, Christopher Semturs, S. Sara Mahdavi, Juraj Gottweis, Alan Karthikesalingam, Vivek Natarajan

CoRR, 2024

2023

Self-supervised video pretraining yields robust and more human-aligned visual representations.

Nikhil Parthasarathy, S. M. Ali Eslami, João Carreira, Olivier J. Hénaff

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football".

Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess

Dataset, August, 2022

From motor control to team play in simulated humanoid football.

Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess

Sci. Robotics, 2022

Self-supervised video pretraining yields strong image representations.

Nikhil Parthasarathy, S. M. Ali Eslami, João Carreira, Olivier J. Hénaff

CoRR, 2022

From data to functa: Your data point is a function and you should treat it like one.

Emilien Dupont, Hyunjik Kim, S. M. Ali Eslami, Danilo J. Rezende, Dan Rosenbaum

CoRR, 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

Proceedings of the International Conference on Machine Learning, 2022

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

J. Artif. Intell. Res., 2021

Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs.

Dan Rosenbaum, Marta Garnelo, Michal Zielinski, Charlie Beattie, Ellen Clancy, Andrea Huber, Pushmeet Kohli, Andrew W. Senior, John Jumper, Carl Doersch, S. M. Ali Eslami, Olaf Ronneberger, Jonas Adler

CoRR, 2021

Generative Art Using Neural Visual Grammars and Dual Encoders.

Chrisantha Fernando, S. M. Ali Eslami, Jean-Baptiste Alayrac, Piotr Mirowski, Dylan Banarse, Simon Osindero

CoRR, 2021

Multimodal Few-Shot Learning with Frozen Language Models.

Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, S. M. Ali Eslami, Oriol Vinyals, Felix Hill

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 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 A. Riedmiller, S. M. Ali Eslami, Nicolas Heess

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Contrastive Training for Improved Out-of-Distribution Detection.

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

CoRR, 2020

PolyGen: An Autoregressive Generative Model of 3D Meshes.

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

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Unsupervised Doodling and Painting with Improved SPIRAL.

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

CoRR, 2019

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

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

CoRR, 2019

Data-Efficient Image Recognition with Contrastive Predictive Coding.

Olivier J. Hénaff, Aravind Srinivas, Jeffrey De Fauw, Ali Razavi, Carl Doersch, S. M. Ali Eslami, Aäron van den Oord

CoRR, 2019

Meta-Learning surrogate models for sequential decision making.

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

CoRR, 2019

Attentive Neural Processes.

Hyunjik Kim, Andriy Mnih, Jonathan Schwarz, Marta Garnelo, S. M. Ali Eslami, Dan Rosenbaum, Oriol Vinyals, Yee Whye Teh

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning.

Aishwarya Agrawal, Mateusz Malinowski, Felix Hill, S. M. Ali Eslami, Oriol Vinyals, Tejas Kulkarni

CoRR, 2018

Learning models for visual 3D localization with implicit mapping.

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

CoRR, 2018

Consistent Generative Query Networks.

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

CoRR, 2018

Encoding Spatial Relations from Natural Language.

Tiago Ramalho, Tomás Kociský, Frederic Besse, S. M. Ali Eslami, Gábor Melis, Fabio Viola, Phil Blunsom, Karl Moritz Hermann

CoRR, 2018

Neural Processes.

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

CoRR, 2018

Kickstarting Deep Reinforcement Learning.

Simon Schmitt, Jonathan J. Hudson, Augustin Zídek, Simon Osindero, Carl Doersch, Wojciech M. Czarnecki, Joel Z. Leibo, Heinrich Küttler, Andrew Zisserman, Karen Simonyan, S. M. Ali Eslami

CoRR, 2018

Learning and Querying Fast Generative Models for Reinforcement Learning.

Lars Buesing, Theophane Weber, Sébastien Racanière, S. M. Ali Eslami, Danilo Jimenez Rezende, David P. Reichert, Fabio Viola, Frederic Besse, Karol Gregor, Demis Hassabis, Daan Wierstra

CoRR, 2018

A Probabilistic U-Net for Segmentation of Ambiguous Images.

Simon 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

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Machine Theory of Mind.

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

Proceedings of the 35th International Conference on Machine Learning, 2018

Conditional Neural Processes.

Marta Garnelo, Dan Rosenbaum, Christopher Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo Jimenez Rezende, S. M. Ali Eslami

Proceedings of the 35th International Conference on Machine Learning, 2018

Synthesizing Programs for Images using Reinforced Adversarial Learning.

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

Proceedings of the 35th International Conference on Machine Learning, 2018

Generative Temporal Models with Spatial Memory for Partially Observed Environments.

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

Proceedings of the 35th International Conference on Machine Learning, 2018

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

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

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Emergence of Locomotion Behaviours in Rich Environments.

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

CoRR, 2017

2016

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

S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, Koray Kavukcuoglu, Geoffrey E. Hinton

CoRR, 2016

Unsupervised Learning of 3D Structure from Images.

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

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 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

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

The Pascal Visual Object Classes Challenge: A Retrospective.

Mark Everingham, S. M. Ali Eslami, Luc Van Gool, Christopher K. I. Williams, John M. Winn, Andrew Zisserman

Int. J. Comput. Vis., 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

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Consensus Message Passing for Layered Graphical Models.

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

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

The Shape Boltzmann Machine: A Strong Model of Object Shape.

S. M. Ali Eslami, Nicolas Heess, Christopher K. I. Williams, John M. Winn

Int. J. Comput. Vis., 2014

Just-In-Time Learning for Fast and Flexible Inference.

S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John M. Winn

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2012

A Generative Model for Parts-based Object Segmentation.

S. M. Ali Eslami, Christopher K. I. Williams

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

The Shape Boltzmann Machine: A strong model of object shape.

S. M. Ali Eslami, Nicolas Heess, John M. Winn

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012