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Nicolas Sonnerat
Nicolas Sonnerat
DeepMind
Adresă de e-mail confirmată pe google.com
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Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ...
arXiv preprint arXiv:2312.11805, 2023
33082023
Value-decomposition networks for cooperative multi-agent learning
P Sunehag, G Lever, A Gruslys, WM Czarnecki, V Zambaldi, M Jaderberg, ...
arXiv preprint arXiv:1706.05296, 2017
20822017
Human-level performance in 3D multiplayer games with population-based reinforcement learning
M Jaderberg, WM Czarnecki, I Dunning, L Marris, G Lever, AG Castaneda, ...
Science 364 (6443), 859-865, 2019
8842019
Solving mixed integer programs using neural networks
V Nair, S Bartunov, F Gimeno, I Von Glehn, P Lichocki, I Lobov, ...
arXiv preprint arXiv:2012.13349, 2020
3272020
Deep reinforcement learning and the deadly triad
H Van Hasselt, Y Doron, F Strub, M Hessel, N Sonnerat, J Modayil
arXiv preprint arXiv:1812.02648, 2018
2842018
Human-level performance in first-person multiplayer games with population-based deep reinforcement learning
M Jaderberg, WM Czarnecki, I Dunning, L Marris, G Lever, AG Castaneda, ...
arXiv preprint arXiv:1807.01281, 2018
1772018
Scan: Learning hierarchical compositional visual concepts
I Higgins, N Sonnerat, L Matthey, A Pal, CP Burgess, M Bosnjak, ...
arXiv preprint arXiv:1707.03389, 2017
1462017
Gemma scope: Open sparse autoencoders everywhere all at once on gemma 2
T Lieberum, S Rajamanoharan, A Conmy, L Smith, N Sonnerat, V Varma, ...
arXiv preprint arXiv:2408.05147, 2024
652024
Learning a large neighborhood search algorithm for mixed integer programs
N Sonnerat, P Wang, I Ktena, S Bartunov, V Nair
arXiv preprint arXiv:2107.10201, 2021
592021
Value-decomposition networks for cooperative multi-agent learning. arXiv 2017
P Sunehag, G Lever, A Gruslys, WM Czarnecki, V Zambaldi, M Jaderberg, ...
arXiv preprint arXiv:1706.05296, 2017
432017
Jumping ahead: Improving reconstruction fidelity with jumprelu sparse autoencoders
S Rajamanoharan, T Lieberum, N Sonnerat, A Conmy, V Varma, J Kramár, ...
arXiv preprint arXiv:2407.14435, 2024
352024
Scan: learning abstract hierarchical compositional visual concepts
I Higgins, N Sonnerat, L Matthey, A Pal, CP Burgess, M Botvinick, ...
arXiv preprint arXiv:1707.03389, 2017
292017
Learning visual concepts using neural networks
A Lerchner, I Higgins, N Sonnerat, AT Pal, D Hassabis, ...
US Patent 11,354,823, 2022
142022
Maximum flows on disjoint paths
G Naves, N Sonnerat, A Vetta
International Workshop on Randomization and Approximation Techniques in …, 2010
62010
Finding increasingly large extremal graphs with alphazero and tabu search
A Mehrabian, A Anand, H Kim, N Sonnerat, M Balog, G Comanici, ...
arXiv preprint arXiv:2311.03583, 2023
52023
Galaxy cutsets in graphs
N Sonnerat, A Vetta
Journal of combinatorial optimization 19, 415-427, 2010
32010
Defending planar graphs against star-cutsets
N Sonnerat, A Vetta
Electronic Notes in Discrete Mathematics 34, 107-111, 2009
32009
Network connectivity and malicious attacks
N Sonnerat, A Vetta
preprint, 2007
32007
Solving mixed integer programs using neural networks
S Bartunov, FAG Gil, IK von Glehn, P Lichocki, I Lobov, V Nair, ...
US Patent App. 18/267,363, 2024
2024
Learning visual concepts using neural networks
A Lerchner, I Higgins, N Sonnerat, AT Pal, D Hassabis, ...
US Patent 11,769,057, 2023
2023
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