Nicolas Sonnerat

According to our database, Nicolas Sonnerat authored at least 14 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2.

Tom Lieberum, Senthooran Rajamanoharan, Arthur Conmy, Lewis Smith, Nicolas Sonnerat, Vikrant Varma, János Kramár, Anca D. Dragan, Rohin Shah, Neel Nanda

CoRR, 2024

Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders.

Senthooran Rajamanoharan, Tom Lieberum, Nicolas Sonnerat, Arthur Conmy, Vikrant Varma, János Kramár, Neel Nanda

CoRR, 2024

Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search.

Abbas Mehrabian, Ankit Anand, Hyunjik Kim, Nicolas Sonnerat, Matej Balog, Gheorghe Comanici, Tudor Berariu, Andrew Lee, Anian Ruoss, Anna Bulanova, Daniel Toyama, Sam Blackwell, Bernardino Romera-Paredes, Petar Velickovic, Laurent Orseau, Joonkyung Lee, Anurag Murty Naredla, Doina Precup, Adam Zsolt Wagner

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2021

Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs.

Nicolas Sonnerat, Pengming Wang, Ira Ktena, Sergey Bartunov, Vinod Nair

CoRR, 2021

2020

Solving Mixed Integer Programs Using Neural Networks.

Vinod Nair, Sergey Bartunov, Felix Gimeno, Ingrid von Glehn, Pawel Lichocki, Ivan Lobov, Brendan O'Donoghue, Nicolas Sonnerat, Christian Tjandraatmadja, Pengming Wang, Ravichandra Addanki, Tharindi Hapuarachchi, Thomas Keck, James Keeling, Pushmeet Kohli, Ira Ktena, Yujia Li, Oriol Vinyals, Yori Zwols

CoRR, 2020

2018

Deep Reinforcement Learning and the Deadly Triad.

Hado van Hasselt, Yotam Doron, Florian Strub, Matteo Hessel, Nicolas Sonnerat, Joseph Modayil

CoRR, 2018

Human-level performance in first-person multiplayer games with population-based deep reinforcement learning.

Max Jaderberg, Wojciech M. Czarnecki, Iain Dunning, Luke Marris, Guy Lever, Antonio García Castañeda, Charles Beattie, Neil C. Rabinowitz, Ari S. Morcos, Avraham Ruderman, Nicolas Sonnerat, Tim Green, Louise Deason, Joel Z. Leibo, David Silver, Demis Hassabis, Koray Kavukcuoglu, Thore Graepel

CoRR, 2018

SCAN: Learning Hierarchical Compositional Visual Concepts.

Irina Higgins, Nicolas Sonnerat, Loic Matthey, Arka Pal, Christopher P. Burgess, Matko Bosnjak, Murray Shanahan, Matthew M. Botvinick, Demis Hassabis, Alexander Lerchner

Proceedings of the 6th International Conference on Learning Representations, 2018

Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward.

Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinícius Flores Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017

Value-Decomposition Networks For Cooperative Multi-Agent Learning.

Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinícius Flores Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel

CoRR, 2017

SCAN: Learning Abstract Hierarchical Compositional Visual Concepts.

Irina Higgins, Nicolas Sonnerat, Loïc Matthey, Arka Pal, Christopher P. Burgess, Matthew M. Botvinick, Demis Hassabis, Alexander Lerchner

CoRR, 2017

2010

Galaxy cutsets in graphs.

Nicolas Sonnerat, Adrian Vetta

J. Comb. Optim., 2010

Maximum Flows on Disjoint Paths.

Guyslain Naves, Nicolas Sonnerat, Adrian Vetta

Proceedings of the Approximation, 2010

2009

Defending Planar Graphs against Star-Cutsets.

Nicolas Sonnerat, Adrian Vetta

Electron. Notes Discret. Math., 2009