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ORCIDS. M. Ali Eslami
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- affiliation: Google DeepMind, London, UK
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Journal Articles
- 2022
[j4]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:
From motor control to team play in simulated humanoid football. Sci. Robotics 7(69) (2022)- 2021
- [j3]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:
Game Plan: What AI can do for Football, and What Football can do for AI. J. Artif. Intell. Res. 71: 41-88 (2021) - 2015
- [j2]Mark Everingham, S. M. Ali Eslami, Luc Van Gool, Christopher K. I. Williams, John M. Winn, Andrew Zisserman:
The Pascal Visual Object Classes Challenge: A Retrospective. Int. J. Comput. Vis. 111(1): 98-136 (2015) - 2014
- [j1]S. M. Ali Eslami, Nicolas Heess, Christopher K. I. Williams, John M. Winn:
The Shape Boltzmann Machine: A Strong Model of Object Shape. Int. J. Comput. Vis. 107(2): 155-176 (2014)
Conference and Workshop Papers
- 2023
- [c19]Nikhil Parthasarathy, S. M. Ali Eslami, João Carreira, Olivier J. Hénaff:
Self-supervised video pretraining yields robust and more human-aligned visual representations. NeurIPS 2023 - 2022
- [c18]Emilien Dupont, Hyunjik Kim, S. M. Ali Eslami, Danilo Jimenez Rezende, Dan Rosenbaum:
From data to functa: Your data point is a function and you can treat it like one. ICML 2022: 5694-5725 - 2021
- [c17]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:
Towards Real Robot Learning in the Wild: A Case Study in Bipedal Locomotion. CoRL 2021: 1502-1511 - [c16]Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, S. M. Ali Eslami, Oriol Vinyals, Felix Hill:
Multimodal Few-Shot Learning with Frozen Language Models. NeurIPS 2021: 200-212 - 2020
- [c15]Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter W. Battaglia:
PolyGen: An Autoregressive Generative Model of 3D Meshes. ICML 2020: 7220-7229 - 2019
- [c14]Hyunjik Kim, Andriy Mnih, Jonathan Schwarz, Marta Garnelo, S. M. Ali Eslami, Dan Rosenbaum, Oriol Vinyals, Yee Whye Teh:
Attentive Neural Processes. ICLR (Poster) 2019 - 2018
- [c13]Scott E. Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo J. Rezende, Oriol Vinyals, Nando de Freitas:
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. ICLR (Poster) 2018 - [c12]Marco Fraccaro, Danilo Jimenez Rezende, Yori Zwols, Alexander Pritzel, S. M. Ali Eslami, Fabio Viola:
Generative Temporal Models with Spatial Memory for Partially Observed Environments. ICML 2018: 1544-1553 - [c11]Yaroslav Ganin, Tejas Kulkarni, Igor Babuschkin, S. M. Ali Eslami, Oriol Vinyals:
Synthesizing Programs for Images using Reinforced Adversarial Learning. ICML 2018: 1652-1661 - [c10]Marta Garnelo, Dan Rosenbaum, Christopher Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo Jimenez Rezende, S. M. Ali Eslami:
Conditional Neural Processes. ICML 2018: 1690-1699 - [c9]Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew M. Botvinick:
Machine Theory of Mind. ICML 2018: 4215-4224 - [c8]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:
A Probabilistic U-Net for Segmentation of Ambiguous Images. NeurIPS 2018: 6965-6975 - 2016
- [c7]S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Koray Kavukcuoglu, Geoffrey E. Hinton:
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models. NIPS 2016: 3225-3233 - [c6]Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter W. Battaglia, Max Jaderberg, Nicolas Heess:
Unsupervised Learning of 3D Structure from Images. NIPS 2016: 4997-5005 - 2015
- [c5]Varun Jampani, S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John M. Winn:
Consensus Message Passing for Layered Graphical Models. AISTATS 2015 - [c4]Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltán Szabó:
Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages. UAI 2015: 405-414 - 2014
- [c3]S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John M. Winn:
Just-In-Time Learning for Fast and Flexible Inference. NIPS 2014: 154-162 - 2012
- [c2]S. M. Ali Eslami, Nicolas Heess, John M. Winn:
The Shape Boltzmann Machine: A strong model of object shape. CVPR 2012: 406-413 - [c1]S. M. Ali Eslami, Christopher K. I. Williams:
A Generative Model for Parts-based Object Segmentation. NIPS 2012: 100-107
Informal and Other Publications
- 2024
- [i34]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:
Capabilities of Gemini Models in Medicine. CoRR abs/2404.18416 (2024) - [i33]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:
Advancing Multimodal Medical Capabilities of Gemini. CoRR abs/2405.03162 (2024) - 2022
- [i32]Emilien Dupont, Hyunjik Kim, S. M. Ali Eslami, Danilo J. Rezende, Dan Rosenbaum:
From data to functa: Your data point is a function and you should treat it like one. CoRR abs/2201.12204 (2022) - [i31]Nikhil Parthasarathy, S. M. Ali Eslami, João Carreira, Olivier J. Hénaff:
Self-supervised video pretraining yields strong image representations. CoRR abs/2210.06433 (2022) - 2021
- [i30]Chrisantha Fernando, S. M. Ali Eslami, Jean-Baptiste Alayrac, Piotr Mirowski, Dylan Banarse, Simon Osindero:
Generative Art Using Neural Visual Grammars and Dual Encoders. CoRR abs/2105.00162 (2021) - [i29]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:
From Motor Control to Team Play in Simulated Humanoid Football. CoRR abs/2105.12196 (2021) - [i28]Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, S. M. Ali Eslami, Oriol Vinyals, Felix Hill:
Multimodal Few-Shot Learning with Frozen Language Models. CoRR abs/2106.13884 (2021) - [i27]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:
Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs. CoRR abs/2106.14108 (2021) - 2020
- [i26]Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter W. Battaglia:
PolyGen: An Autoregressive Generative Model of 3D Meshes. CoRR abs/2002.10880 (2020) - [i25]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:
Contrastive Training for Improved Out-of-Distribution Detection. CoRR abs/2007.05566 (2020) - [i24]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:
Game Plan: What AI can do for Football, and What Football can do for AI. CoRR abs/2011.09192 (2020) - 2019
- [i23]Hyunjik Kim, Andriy Mnih, Jonathan Schwarz, Marta Garnelo, S. M. Ali Eslami, Dan Rosenbaum, Oriol Vinyals, Yee Whye Teh:
Attentive Neural Processes. CoRR abs/1901.05761 (2019) - [i22]Alexandre Galashov, Jonathan Schwarz, Hyunjik Kim, Marta Garnelo, David Saxton, Pushmeet Kohli, S. M. Ali Eslami, Yee Whye Teh:
Meta-Learning surrogate models for sequential decision making. CoRR abs/1903.11907 (2019) - [i21]Olivier J. Hénaff, Aravind Srinivas, Jeffrey De Fauw, Ali Razavi, Carl Doersch, S. M. Ali Eslami, Aäron van den Oord:
Data-Efficient Image Recognition with Contrastive Predictive Coding. CoRR abs/1905.09272 (2019) - [i20]Simon A. A. Kohl, Bernardino Romera-Paredes, Klaus H. Maier-Hein, Danilo Jimenez Rezende, S. M. Ali Eslami, Pushmeet Kohli, Andrew Zisserman, Olaf Ronneberger:
A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities. CoRR abs/1905.13077 (2019) - [i19]John F. J. Mellor, Eunbyung Park, Yaroslav Ganin, Igor Babuschkin, Tejas Kulkarni, Dan Rosenbaum, Andy Ballard, Theophane Weber, Oriol Vinyals, S. M. Ali Eslami:
Unsupervised Doodling and Painting with Improved SPIRAL. CoRR abs/1910.01007 (2019) - 2018
- [i18]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:
Learning and Querying Fast Generative Models for Reinforcement Learning. CoRR abs/1802.03006 (2018) - [i17]Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew M. Botvinick:
Machine Theory of Mind. CoRR abs/1802.07740 (2018) - [i16]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:
Kickstarting Deep Reinforcement Learning. CoRR abs/1803.03835 (2018) - [i15]Yaroslav Ganin, Tejas Kulkarni, Igor Babuschkin, S. M. Ali Eslami, Oriol Vinyals:
Synthesizing Programs for Images using Reinforced Adversarial Learning. CoRR abs/1804.01118 (2018) - [i14]Marco Fraccaro, Danilo Jimenez Rezende, Yori Zwols, Alexander Pritzel, S. M. Ali Eslami, Fabio Viola:
Generative Temporal Models with Spatial Memory for Partially Observed Environments. CoRR abs/1804.09401 (2018) - [i13]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:
A Probabilistic U-Net for Segmentation of Ambiguous Images. CoRR abs/1806.05034 (2018) - [i12]Marta Garnelo, Dan Rosenbaum, Chris J. Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo J. Rezende, S. M. Ali Eslami:
Conditional Neural Processes. CoRR abs/1807.01613 (2018) - [i11]Marta Garnelo, Jonathan Schwarz, Dan Rosenbaum, Fabio Viola, Danilo J. Rezende, S. M. Ali Eslami, Yee Whye Teh:
Neural Processes. CoRR abs/1807.01622 (2018) - [i10]Tiago Ramalho, Tomás Kociský, Frederic Besse, S. M. Ali Eslami, Gábor Melis, Fabio Viola, Phil Blunsom, Karl Moritz Hermann:
Encoding Spatial Relations from Natural Language. CoRR abs/1807.01670 (2018) - [i9]Ananya Kumar, S. M. Ali Eslami, Danilo J. Rezende, Marta Garnelo, Fabio Viola, Edward Lockhart, Murray Shanahan:
Consistent Generative Query Networks. CoRR abs/1807.02033 (2018) - [i8]Dan Rosenbaum, Frederic Besse, Fabio Viola, Danilo J. Rezende, S. M. Ali Eslami:
Learning models for visual 3D localization with implicit mapping. CoRR abs/1807.03149 (2018) - [i7]Aishwarya Agrawal, Mateusz Malinowski, Felix Hill, S. M. Ali Eslami, Oriol Vinyals, Tejas Kulkarni:
Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning. CoRR abs/1812.00898 (2018) - 2017
- [i6]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:
Emergence of Locomotion Behaviours in Rich Environments. CoRR abs/1707.02286 (2017) - [i5]Scott E. Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo Jimenez Rezende, Oriol Vinyals, Nando de Freitas:
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. CoRR abs/1710.10304 (2017) - 2016
- [i4]S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, Koray Kavukcuoglu, Geoffrey E. Hinton:
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models. CoRR abs/1603.08575 (2016) - [i3]Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter W. Battaglia, Max Jaderberg, Nicolas Heess:
Unsupervised Learning of 3D Structure from Images. CoRR abs/1607.00662 (2016) - 2015
- [i2]Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltán Szabó:
Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages. CoRR abs/1503.02551 (2015) - 2014
- [i1]Varun Jampani, S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John M. Winn:
Consensus Message Passing for Layered Graphical Models. CoRR abs/1410.7452 (2014)
Coauthor Index
Danilo Jimenez Rezende
aka: Danilo J. Rezende
aka: Danilo J. Rezende
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