Seuraa
Frederic Besse
Frederic Besse
DeepMind
Vahvistettu sähköpostiosoite verkkotunnuksessa google.com
Nimike
Viittaukset
Viittaukset
Vuosi
Neural scene representation and rendering
SMA Eslami, D Jimenez Rezende, F Besse, F Viola, AS Morcos, ...
Science 360 (6394), 1204-1210, 2018
7562018
Towards conceptual compression
K Gregor, F Besse, D Jimenez Rezende, I Danihelka, D Wierstra
Advances in neural information processing systems 29, 2016
345*2016
Pmbp: Patchmatch belief propagation for correspondence field estimation
F Besse, C Rother, A Fitzgibbon, J Kautz
International Journal of Computer Vision 110, 2-13, 2014
2892014
Temporal difference variational auto-encoder
K Gregor, G Papamakarios, F Besse, L Buesing, T Weber
arXiv preprint arXiv:1806.03107, 2018
1562018
Convolution by evolution: Differentiable pattern producing networks
C Fernando, D Banarse, M Reynolds, F Besse, D Pfau, M Jaderberg, ...
Proceedings of the Genetic and Evolutionary Computation Conference 2016, 109-116, 2016
1382016
Shaping belief states with generative environment models for rl
K Gregor, D Jimenez Rezende, F Besse, Y Wu, H Merzic, A van den Oord
Advances in Neural Information Processing Systems 32, 2019
1232019
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
1192018
Highly overparameterized optical flow using patchmatch belief propagation
M Hornáček, F Besse, J Kautz, A Fitzgibbon, C Rother
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
442014
Causally correct partial models for reinforcement learning
DJ Rezende, I Danihelka, G Papamakarios, NR Ke, R Jiang, T Weber, ...
arXiv preprint arXiv:2002.02836, 2020
362020
Demis Hassabis, et al. 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 2, 2018
362018
Learning models for visual 3d localization with implicit mapping
D Rosenbaum, F Besse, F Viola, DJ Rezende, SM Eslami
arXiv preprint arXiv:1807.03149, 2018
322018
TF-Replicator: Distributed machine learning for researchers
P Buchlovsky, D Budden, D Grewe, C Jones, J Aslanides, F Besse, ...
arXiv preprint arXiv:1902.00465, 2019
252019
Encoding spatial relations from natural language
T Ramalho, T Kočiský, F Besse, SM Eslami, G Melis, F Viola, P Blunsom, ...
arXiv preprint arXiv:1807.01670, 2018
142018
Self-organizing intelligent matter: A blueprint for an ai generating algorithm
K Gregor, F Besse
arXiv preprint arXiv:2101.07627, 2021
122021
Scaling instructable agents across many simulated worlds
MA Raad, A Ahuja, C Barros, F Besse, A Bolt, A Bolton, B Brownfield, ...
arXiv preprint arXiv:2404.10179, 2024
112024
Bethanie Brownfield, Gavin Buttimore, Max Cant, Sarah Chakera, et al. Scaling instructable agents across many simulated worlds
M Abi Raad, A Ahuja, C Barros, F Besse, A Bolt, A Bolton
arXiv preprint arXiv:2404.10179, 2024
82024
PatchMatch Belief Propagation for Correspondence Field Estimation and Its Applications
FO Besse
UCL (University College London), 2013
82013
Scaling instructable agents across many simulated worlds
M Abi Raad, A Ahuja, C Barros, F Besse, A Bolt, A Bolton, B Brownfield, ...
arXiv e-prints, arXiv: 2404.10179, 2024
42024
Learning to encode spatial relations from natural language
T Ramalho, T Kocisky, F Besse, SMA Eslami, G Melis, F Viola, P Blunsom, ...
42018
Scene understanding and generation using neural networks
DJ Rezende, SM Eslami, K Gregor, FO Besse
US Patent App. 18/164,021, 2023
2023
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Artikkelit 1–20