Andrew Jaegle
Andrew Jaegle
Research Scientist, DeepMind
Email verificata su google.com - Home page
Titolo
Citata da
Citata da
Anno
Hamiltonian generative networks
P Toth, DJ Rezende, A Jaegle, S Racanière, A Botev, I Higgins
International Conference on Learning Representations (ICLR), 2020
642020
Direct control of visual perception with phase-specific modulation of posterior parietal cortex
A Jaegle, T Ro
Journal of cognitive neuroscience 26 (2), 422-432, 2014
492014
Emergence of invariant representation of vocalizations in the auditory cortex
IM Carruthers, DA Laplagne, A Jaegle, JJ Briguglio, ...
Journal of neurophysiology 114 (5), 2726-2740, 2015
452015
Fast, robust, continuous monocular egomotion computation
A Jaegle, S Phillips, K Daniilidis
2016 IEEE International Conference on Robotics and Automation (ICRA), 773-780, 2016
272016
Population response magnitude variation in inferotemporal cortex predicts image memorability
A Jaegle, V Mehrpour, Y Mohsenzadeh, T Meyer, A Oliva, N Rust
Elife 8, e47596, 2019
182019
Learning what you can do before doing anything
O Rybkin, K Pertsch, KG Derpanis, K Daniilidis, A Jaegle
International Conference on Learning Representations (ICLR), 2019
18*2019
Visual novelty, curiosity, and intrinsic reward in machine learning and the brain
A Jaegle, V Mehrpour, N Rust
Current opinion in neurobiology 58, 167-174, 2019
152019
Understanding image motion with group representations
A Jaegle, S Phillips, D Ippolito, K Daniilidis
International Conference on Learning Representations (ICLR), 2018
62018
Keyframing the Future: Keyframe Discovery for Visual Prediction and Planning
K Pertsch, O Rybkin, J Yang, KG Derpanis, K Daniilidis, J Lim, A Jaegle
Learning for Dynamics & Control (L4DC), 2020
5*2020
Second order receptive field properties of simple and complex cells support a new standard model of thalamocortical circuitry in V1
M Sedigh-Sarvestani, I Fernandez-Lamo, A Jaegle, MM Taylor
Journal of Neuroscience 34 (34), 11177-11179, 2014
42014
Physically embedded planning problems: New challenges for reinforcement learning
M Mirza, A Jaegle, JJ Hunt, A Guez, S Tunyasuvunakool, A Muldal, ...
arXiv preprint arXiv:2009.05524, 2020
22020
Game Plan: What AI can do for Football, and What Football can do for AI
K Tuyls, S Omidshafiei, P Muller, Z Wang, J Connor, D Hennes, I Graham, ...
Journal of Artificial Intelligence Research 71, 41-88, 2021
12021
Perceiver: General Perception with Iterative Attention
A Jaegle, F Gimeno, A Brock, A Zisserman, O Vinyals, J Carreira
arXiv preprint arXiv:2103.03206, 2021
12021
Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban
P Karkus, M Mirza, A Guez, A Jaegle, T Lillicrap, L Buesing, N Heess, ...
ICLR Workshop "Beyond 'tabula rasa' in reinforcement learning", 2020
12020
Predicting the Future with Transformational States
A Jaegle, O Rybkin, KG Derpanis, K Daniilidis
arXiv preprint arXiv:1803.09760, 2018
12018
A neural correlate of image memorability in inferotemporal cortex
V Mehrpour, Y Mohsenzadeh, A Jaegle, T Meyer, A Oliva, NC Rust
Journal of Vision 19 (10), 91c-91c, 2019
2019
Codes, functions, and causes: A critique of Brette's conceptual analysis of coding
D Barack, A Jaegle
Behavioral and Brain Sciences 42, 2019
2019
Learning, Moving, And Predicting With Global Motion Representations
AC Jaegle
2018
Temporal Difference and Return Optimism in Cooperative Multi-Agent Reinforcement Learning
M Rowland, S Omidshafiei, D Hennes, W Dabney, A Jaegle, P Muller, ...
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
Articoli 1–19