Andrew Jaegle

44 papers A* 8Misc 1Journal 30Unranked 5
YearRankTypeTitle / Venue / Authors
2025 J jnl
Seeing Voices: Generating A-Roll Video from Audio with Mirage.
CoRR
Aditi Sundararaman, Amogh Adishesha, Andrew Jaegle, Dan Bigioi, Hyoung-Kyu Song, Jon Kyl, Justin Mao, Kevin Lan, Mojtaba Komeili, Shahrukh Athar, Sheila Babayan, Stanislau Beliasau, William Buchwalter
2024 A* conf
SODA: Bottleneck Diffusion Models for Representation Learning.
CVPR
Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner
2023 J jnl
Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task.
Trans. Mach. Learn. Res.
Jannik Kossen, Catalina Cangea, Eszter Vértes, Andrew Jaegle, Viorica Patraucean, Ira Ktena, Nenad Tomasev, Danielle Belgrave
2023 J jnl
SODA: Bottleneck Diffusion Models for Representation Learning.
CoRR
Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner
2023 J jnl
Transframer: Arbitrary Frame Prediction with Generative Models.
Trans. Mach. Learn. Res.
Charlie Nash, João Carreira, Jacob C. Walker, Iain Barr, Andrew Jaegle, Mateusz Malinowski, Peter W. Battaglia
2023 J jnl
Zorro: the masked multimodal transformer.
CoRR
Adrià Recasens, Jason Lin, João Carreira, Andrew Jaegle, Luyu Wang, Jean-Baptiste Alayrac, Pauline Luc, Antoine Miech, Lucas Smaira, Ross Hemsley, Andrew Zisserman
2022 J jnl
Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task.
CoRR
Jannik Kossen, Catalina Cangea, Eszter Vértes, Andrew Jaegle, Viorica Patraucean, Ira Ktena, Nenad Tomasev, Danielle Belgrave
2022 J jnl
Extended Intelligence.
CoRR
David L. Barack, Andrew Jaegle
2022 A* conf
General-purpose, long-context autoregressive modeling with Perceiver AR.
ICML
Curtis Hawthorne, Andrew Jaegle, Catalina Cangea, Sebastian Borgeaud, Charlie Nash, Mateusz Malinowski, Sander Dieleman, Oriol Vinyals, Matthew M. Botvinick, Ian Simon, Hannah Sheahan, Neil Zeghidour, Jean-Baptiste Alayrac, João Carreira, Jesse H. Engel
2022 J jnl
General-purpose, long-context autoregressive modeling with Perceiver AR.
CoRR
Curtis Hawthorne, Andrew Jaegle, Catalina Cangea, Sebastian Borgeaud, Charlie Nash, Mateusz Malinowski, Sander Dieleman, Oriol Vinyals, Matthew M. Botvinick, Ian Simon, Hannah Sheahan, Neil Zeghidour, Jean-Baptiste Alayrac, João Carreira, Jesse H. Engel
2022 J jnl
Hierarchical Perceiver.
CoRR
João Carreira, Skanda Koppula, Daniel Zoran, Adrià Recasens, Catalin Ionescu, Olivier J. Hénaff, Evan Shelhamer, Relja Arandjelovic, Matthew M. Botvinick, Oriol Vinyals, Karen Simonyan, Andrew Zisserman, Andrew Jaegle
2022 — conf
Object Discovery and Representation Networks.
ECCV (27)
Olivier J. Hénaff, Skanda Koppula, Evan Shelhamer, Daniel Zoran, Andrew Jaegle, Andrew Zisserman, João Carreira, Relja Arandjelovic
2022 J jnl
Object discovery and representation networks.
CoRR
Olivier J. Hénaff, Skanda Koppula, Evan Shelhamer, Daniel Zoran, Andrew Jaegle, Andrew Zisserman, João Carreira, Relja Arandjelovic
2022 A* conf
Perceiver IO: A General Architecture for Structured Inputs & Outputs.
ICLR
Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira
2022 Misc conf
Towards Learning Universal Audio Representations.
ICASSP
Luyu Wang, Pauline Luc, Yan Wu, Adrià Recasens, Lucas Smaira, Andrew Brock, Andrew Jaegle, Jean-Baptiste Alayrac, Sander Dieleman, João Carreira, Aäron van den Oord
2022 J jnl
Transframer: Arbitrary Frame Prediction with Generative Models.
CoRR
Charlie Nash, João Carreira, Jacob C. Walker, Iain Barr, Andrew Jaegle, Mateusz Malinowski, Peter W. Battaglia
2022 J jnl
Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods.
CoRR
Skanda Koppula, Yazhe Li, Evan Shelhamer, Andrew Jaegle, Nikhil Parthasarathy, Relja Arandjelovic, João Carreira, Olivier J. Hénaff
2021 J jnl
Game Plan: What AI can do for Football, and What Football can do for AI.
J. Artif. Intell. Res.
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
2021 A* conf
Imitation by Predicting Observations.
ICML
Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne
2021 J jnl
Imitation by Predicting Observations.
CoRR
Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne
2021 J jnl
Perceiver IO: A General Architecture for Structured Inputs & Outputs.
CoRR
Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira
2021 A* conf
Perceiver: General Perception with Iterative Attention.
ICML
Andrew Jaegle, Felix Gimeno, Andy Brock, Oriol Vinyals, Andrew Zisserman, João Carreira
2021 J jnl
Perceiver: General Perception with Iterative Attention.
CoRR
Andrew Jaegle, Felix Gimeno, Andrew Brock, Andrew Zisserman, Oriol Vinyals, João Carreira
2021 A* conf
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision.
NeurIPS
Irina Higgins, Peter Wirnsberger, Andrew Jaegle, Aleksandar Botev
2021 J jnl
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision.
CoRR
Irina Higgins, Peter Wirnsberger, Andrew Jaegle, Aleksandar Botev
2021 J jnl
Towards Learning Universal Audio Representations.
CoRR
Luyu Wang, Pauline Luc, Yan Wu, Adrià Recasens, Lucas Smaira, Andrew Brock, Andrew Jaegle, Jean-Baptiste Alayrac, Sander Dieleman, João Carreira, Aäron van den Oord
2021 — conf
Which priors matter? Benchmarking models for learning latent dynamics.
NeurIPS Datasets and Benchmarks
Aleksandar Botev, Andrew Jaegle, Peter Wirnsberger, Daniel Hennes, Irina Higgins
2021 J jnl
Which priors matter? Benchmarking models for learning latent dynamics.
CoRR
Aleksandar Botev, Andrew Jaegle, Peter Wirnsberger, Daniel Hennes, Irina Higgins
2020 J jnl
Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban.
CoRR
Péter Karkus, Mehdi Mirza, Arthur Guez, Andrew Jaegle, Timothy P. Lillicrap, Lars Buesing, Nicolas Heess, Theophane Weber
2020 J jnl
Game Plan: What AI can do for Football, and What Football can do for AI.
CoRR
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
2020 A* conf
Hamiltonian Generative Networks.
ICLR
Peter Toth, Danilo J. Rezende, Andrew Jaegle, Sébastien Racanière, Aleksandar Botev, Irina Higgins
2020 — conf
Keyframing the Future: Keyframe Discovery for Visual Prediction and Planning.
L4DC
Karl Pertsch, Oleh Rybkin, Jingyun Yang, Shenghao Zhou, Konstantinos G. Derpanis, Kostas Daniilidis, Joseph J. Lim, Andrew Jaegle
2020 J jnl
Physically Embedded Planning Problems: New Challenges for Reinforcement Learning.
CoRR
Mehdi Mirza, Andrew Jaegle, Jonathan J. Hunt, Arthur Guez, Saran Tunyasuvunakool, Alistair Muldal, Théophane Weber, Péter Karkus, Sébastien Racanière, Lars Buesing, Timothy P. Lillicrap, Nicolas Heess
2019 J jnl
Codes, Functions, and Causes: A Critique of Brette's Conceptual Analysis of Coding.
CoRR
David L. Barack, Andrew Jaegle
2019 J jnl
Hamiltonian Generative Networks.
CoRR
Peter Toth, Danilo Jimenez Rezende, Andrew Jaegle, Sébastien Racanière, Aleksandar Botev, Irina Higgins
2019 J jnl
KeyIn: Discovering Subgoal Structure with Keyframe-based Video Prediction.
CoRR
Karl Pertsch, Oleh Rybkin, Jingyun Yang, Konstantinos G. Derpanis, Joseph J. Lim, Kostas Daniilidis, Andrew Jaegle
2019 — conf
Learning what you can do before doing anything.
ICLR (Poster)
Oleh Rybkin, Karl Pertsch, Konstantinos G. Derpanis, Kostas Daniilidis, Andrew Jaegle
2018 J jnl
Predicting the Future with Transformational States.
CoRR
Andrew Jaegle, Oleh Rybkin, Konstantinos G. Derpanis, Kostas Daniilidis
2018 — conf
Understanding image motion with group representations.
ICLR (Poster)
Andrew Jaegle, Stephen Phillips, Daphne Ippolito, Kostas Daniilidis
2018 J jnl
Unsupervised Learning of Sensorimotor Affordances by Stochastic Future Prediction.
CoRR
Oleh Rybkin, Karl Pertsch, Andrew Jaegle, Konstantinos G. Derpanis, Kostas Daniilidis
2016 J jnl
Fast, Robust, Continuous Monocular Egomotion Computation.
CoRR
Andrew Jaegle, Stephen Phillips, Kostas Daniilidis
2016 A* conf
Fast, robust, continuous monocular egomotion computation.
ICRA
Andrew Jaegle, Stephen Phillips, Kostas Daniilidis
2016 J jnl
Unsupervised learning of image motion by recomposing sequences.
CoRR
Andrew Jaegle, Stephen Phillips, Daphne Ippolito, Kostas Daniilidis
2014 J jnl
Direct Control of Visual Perception with Phase-specific Modulation of Posterior Parietal Cortex.
J. Cogn. Neurosci.
Andrew Jaegle, Tony Ro