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2020 – today
- 2024
[c14]Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner:
SODA: Bottleneck Diffusion Models for Representation Learning. CVPR 2024: 23115-23127- 2023
- [j4]Jannik Kossen, Catalina Cangea, Eszter Vértes, Andrew Jaegle, Viorica Patraucean, Ira Ktena, Nenad Tomasev, Danielle Belgrave:
Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task. Trans. Mach. Learn. Res. 2023 (2023) - [j3]Charlie Nash, João Carreira, Jacob C. Walker, Iain Barr, Andrew Jaegle, Mateusz Malinowski, Peter W. Battaglia:
Transframer: Arbitrary Frame Prediction with Generative Models. Trans. Mach. Learn. Res. 2023 (2023) - [i25]Adrià Recasens, Jason Lin, João Carreira, Andrew Jaegle, Luyu Wang, Jean-Baptiste Alayrac, Pauline Luc, Antoine Miech, Lucas Smaira, Ross Hemsley, Andrew Zisserman:
Zorro: the masked multimodal transformer. CoRR abs/2301.09595 (2023) - [i24]Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner:
SODA: Bottleneck Diffusion Models for Representation Learning. CoRR abs/2311.17901 (2023) - 2022
- [c13]Olivier J. Hénaff, Skanda Koppula, Evan Shelhamer, Daniel Zoran, Andrew Jaegle, Andrew Zisserman, João Carreira, Relja Arandjelovic:
Object Discovery and Representation Networks. ECCV (27) 2022: 123-143 - [c12]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:
Towards Learning Universal Audio Representations. ICASSP 2022: 4593-4597 - [c11]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:
Perceiver IO: A General Architecture for Structured Inputs & Outputs. ICLR 2022 - [c10]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:
General-purpose, long-context autoregressive modeling with Perceiver AR. ICML 2022: 8535-8558 - [i23]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:
General-purpose, long-context autoregressive modeling with Perceiver AR. CoRR abs/2202.07765 (2022) - [i22]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:
Hierarchical Perceiver. CoRR abs/2202.10890 (2022) - [i21]Olivier J. Hénaff, Skanda Koppula, Evan Shelhamer, Daniel Zoran, Andrew Jaegle, Andrew Zisserman, João Carreira, Relja Arandjelovic:
Object discovery and representation networks. CoRR abs/2203.08777 (2022) - [i20]Charlie Nash, João Carreira, Jacob C. Walker, Iain Barr, Andrew Jaegle, Mateusz Malinowski, Peter W. Battaglia:
Transframer: Arbitrary Frame Prediction with Generative Models. CoRR abs/2203.09494 (2022) - [i19]David L. Barack, Andrew Jaegle:
Extended Intelligence. CoRR abs/2209.07449 (2022) - [i18]Skanda Koppula, Yazhe Li, Evan Shelhamer, Andrew Jaegle, Nikhil Parthasarathy, Relja Arandjelovic, João Carreira, Olivier J. Hénaff:
Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods. CoRR abs/2209.15589 (2022) - [i17]Jannik Kossen, Catalina Cangea, Eszter Vértes, Andrew Jaegle, Viorica Patraucean, Ira Ktena, Nenad Tomasev, Danielle Belgrave:
Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task. CoRR abs/2211.05039 (2022) - 2021
- [j2]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) - [c9]Andrew Jaegle, Felix Gimeno, Andy Brock, Oriol Vinyals, Andrew Zisserman, João Carreira:
Perceiver: General Perception with Iterative Attention. ICML 2021: 4651-4664 - [c8]Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne:
Imitation by Predicting Observations. ICML 2021: 4665-4676 - [c7]Aleksandar Botev, Andrew Jaegle, Peter Wirnsberger, Daniel Hennes, Irina Higgins:
Which priors matter? Benchmarking models for learning latent dynamics. NeurIPS Datasets and Benchmarks 2021 - [c6]Irina Higgins, Peter Wirnsberger, Andrew Jaegle, Aleksandar Botev:
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision. NeurIPS 2021: 25591-25605 - [i16]Andrew Jaegle, Felix Gimeno
, Andrew Brock, Andrew Zisserman, Oriol Vinyals, João Carreira:
Perceiver: General Perception with Iterative Attention. CoRR abs/2103.03206 (2021) - [i15]Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne:
Imitation by Predicting Observations. CoRR abs/2107.03851 (2021) - [i14]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:
Perceiver IO: A General Architecture for Structured Inputs & Outputs. CoRR abs/2107.14795 (2021) - [i13]Aleksandar Botev, Andrew Jaegle, Peter Wirnsberger, Daniel Hennes, Irina Higgins:
Which priors matter? Benchmarking models for learning latent dynamics. CoRR abs/2111.05458 (2021) - [i12]Irina Higgins, Peter Wirnsberger, Andrew Jaegle, Aleksandar Botev:
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision. CoRR abs/2111.05986 (2021) - [i11]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:
Towards Learning Universal Audio Representations. CoRR abs/2111.12124 (2021) - 2020
- [c5]Peter Toth, Danilo J. Rezende, Andrew Jaegle, Sébastien Racanière, Aleksandar Botev, Irina Higgins:
Hamiltonian Generative Networks. ICLR 2020 - [c4]Karl Pertsch, Oleh Rybkin, Jingyun Yang, Shenghao Zhou, Konstantinos G. Derpanis, Kostas Daniilidis, Joseph J. Lim, Andrew Jaegle:
Keyframing the Future: Keyframe Discovery for Visual Prediction and Planning. L4DC 2020: 969-979 - [i10]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:
Physically Embedded Planning Problems: New Challenges for Reinforcement Learning. CoRR abs/2009.05524 (2020) - [i9]Péter Karkus, Mehdi Mirza, Arthur Guez, Andrew Jaegle, Timothy P. Lillicrap, Lars Buesing, Nicolas Heess, Theophane Weber:
Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban. CoRR abs/2010.01298 (2020) - [i8]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)
2010 – 2019
- 2019
- [c3]Oleh Rybkin, Karl Pertsch, Konstantinos G. Derpanis, Kostas Daniilidis, Andrew Jaegle:
Learning what you can do before doing anything. ICLR (Poster) 2019 - [i7]Karl Pertsch, Oleh Rybkin, Jingyun Yang, Konstantinos G. Derpanis, Joseph J. Lim, Kostas Daniilidis, Andrew Jaegle:
KeyIn: Discovering Subgoal Structure with Keyframe-based Video Prediction. CoRR abs/1904.05869 (2019) - [i6]David L. Barack, Andrew Jaegle:
Codes, Functions, and Causes: A Critique of Brette's Conceptual Analysis of Coding. CoRR abs/1904.08873 (2019) - [i5]Peter Toth, Danilo Jimenez Rezende, Andrew Jaegle, Sébastien Racanière, Aleksandar Botev, Irina Higgins:
Hamiltonian Generative Networks. CoRR abs/1909.13789 (2019) - 2018
- [c2]Andrew Jaegle, Stephen Phillips, Daphne Ippolito, Kostas Daniilidis:
Understanding image motion with group representations. ICLR (Poster) 2018 - [i4]Andrew Jaegle, Oleh Rybkin, Konstantinos G. Derpanis, Kostas Daniilidis:
Predicting the Future with Transformational States. CoRR abs/1803.09760 (2018) - [i3]Oleh Rybkin, Karl Pertsch, Andrew Jaegle, Konstantinos G. Derpanis, Kostas Daniilidis:
Unsupervised Learning of Sensorimotor Affordances by Stochastic Future Prediction. CoRR abs/1806.09655 (2018) - 2016
- [c1]Andrew Jaegle, Stephen Phillips, Kostas Daniilidis:
Fast, robust, continuous monocular egomotion computation. ICRA 2016: 773-780 - [i2]Andrew Jaegle, Stephen Phillips, Kostas Daniilidis:
Fast, Robust, Continuous Monocular Egomotion Computation. CoRR abs/1602.04886 (2016) - [i1]Andrew Jaegle, Stephen Phillips, Daphne Ippolito, Kostas Daniilidis:
Unsupervised learning of image motion by recomposing sequences. CoRR abs/1612.00472 (2016) - 2014
- [j1]Andrew Jaegle, Tony Ro:
Direct Control of Visual Perception with Phase-specific Modulation of Posterior Parietal Cortex. J. Cogn. Neurosci. 26(2): 422-432 (2014)
Coauthor Index
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last updated on 2024-10-07 02:35 CEST by the dblp team
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