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David P. Reichert
David P. Reichert
Google DeepMind
Verified email at google.com
Title
Cited by
Cited by
Year
Neural scene representation and rendering
SMA Eslami, DJ Rezende, F Besse, F Viola, AS Morcos, M Garnelo, ...
Science 360 (6394), 1204-1210, 2018
6812018
Imagination-augmented agents for deep reinforcement learning
S Racanière, T Weber, D Reichert, L Buesing, A Guez, DJ Rezende, ...
Advances in neural information processing systems, 5690-5701, 2017
674*2017
The predictron: End-to-end learning and planning
D Silver, H van Hasselt, M Hessel, T Schaul, A Guez, T Harley, ...
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
2902017
Relational Deep Reinforcement Learning
V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ...
arXiv preprint arXiv:1806.01830, 2018
2632018
Deep reinforcement learning with relational inductive biases
V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ...
International Conference on Learning Representations, 2018
2092018
Learning and Querying Fast Generative Models for Reinforcement Learning
L Buesing, T Weber, S Racaniere, SM Eslami, D Rezende, DP Reichert, ...
arXiv preprint arXiv:1802.03006, 2018
1332018
Learning model-based planning from scratch
R Pascanu, Y Li, O Vinyals, N Heess, L Buesing, S Racanière, D Reichert, ...
arXiv preprint arXiv:1707.06170, 2017
1162017
Neuronal Synchrony in Complex-Valued Deep Networks
DP Reichert, T Serre
arXiv preprint arXiv:1312.6115, 2013
1092013
Charles Bonnet Syndrome: Evidence for a Generative Model in the Cortex?
DP Reichert, P Seriès, AJ Storkey
PLOS Computational Biology 9 (7), e1003134, 2013
772013
Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model
DP Reichert, P Series, AJ Storkey
Advances in Neural Information Processing Systems 23 (23), 2020-2028, 2010
602010
Automated curricula through setter-solver interactions
S Racaniere, AK Lampinen, A Santoro, DP Reichert, V Firoiu, TP Lillicrap
arXiv preprint arXiv:1909.12892, 2019
522019
Automated curriculum generation through setter-solver interactions
S Racaniere, A Lampinen, A Santoro, D Reichert, V Firoiu, T Lillicrap
International Conference on Learning Representations, 2019
352019
Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents
JX Wang, M King, N Porcel, Z Kurth-Nelson, T Zhu, C Deck, P Choy, ...
arXiv preprint arXiv:2102.02926, 2021
302021
Alchemy: A structured task distribution for meta-reinforcement learning
JX Wang, M King, N Porcel, Z Kurth-Nelson, T Zhu, C Deck, P Choy, ...
arXiv preprint arXiv:2102.02926, 2021
252021
A hierarchical generative model of recurrent object-based attention in the visual cortex
DP Reichert, P Series, AJ Storkey
International Conference on Artificial Neural Networks, 18-25, 2011
222011
Neuronal adaptation for sampling-based probabilistic inference in perceptual bistability
DP Reichert, P Seriès, AJ Storkey
Advances in Neural Information Processing Systems, 2357-2365, 2011
82011
Deep Boltzmann Machines as Hierarchical Generative Models of Perceptual Inference in the Cortex
DP Reichert
PhD thesis, University of Edinburgh, Edinburgh, UK, 2012
52012
Imagination-based agent neural networks
DP Wierstra, Y Li, R Pascanu, PW Battaglia, TG Weber, L Buesing, ...
US Patent App. 16/689,058, 2020
32020
Selectivity for non-accidental properties emerges from learning object transformation sequences
S Parker, D Reichert, T Serre
Journal of Vision 14 (10), 910-910, 2014
22014
Unifying low-level mechanistic and high-level Bayesian explanations of bistable perceptions: neuronal adaptation for cortical inference
DP Reichert, P Series, AJ Storkey
BMC neuroscience 12 (1), P320, 2011
12011
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Articles 1–20