no code implementations • 1 Nov 2023 • David Warde-Farley, Vinod Nair, Yujia Li, Ivan Lobov, Felix Gimeno, Simon Osindero
Since matrix multiplication is the main computational primitive for block Gibbs sampling in an RBM, our approach leads to an elegantly simple algorithm (40 lines of JAX) well-suited for neural network accelerators.
1 code implementation • DeepMind 2022 • Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, Oriol Vinyals
Programming is a powerful and ubiquitous problem-solving tool.
Ranked #1 on Code Generation on CodeContests
10 code implementations • 4 Mar 2021 • Andrew Jaegle, Felix Gimeno, Andrew Brock, Andrew Zisserman, Oriol Vinyals, Joao Carreira
The perception models used in deep learning on the other hand are designed for individual modalities, often relying on domain-specific assumptions such as the local grid structures exploited by virtually all existing vision models.
Ranked #29 on Audio Classification on AudioSet
1 code implementation • 23 Dec 2020 • 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
Our approach constructs two corresponding neural network-based components, Neural Diving and Neural Branching, to use in a base MIP solver such as SCIP.
1 code implementation • 7 Jul 2020 • Yujia Li, Felix Gimeno, Pushmeet Kohli, Oriol Vinyals
We study the problem of learning efficient algorithms that strongly generalize in the framework of neural program induction.
no code implementations • 4 Dec 2019 • Xujie Si, Yujia Li, Vinod Nair, Felix Gimeno
We share this observation in the hope that it helps the SAT community better understand the hardness of random instances used in competitions and inspire other interesting ideas on SAT solving.
no code implementations • ICLR 2020 • Aditya Paliwal, Felix Gimeno, Vinod Nair, Yujia Li, Miles Lubin, Pushmeet Kohli, Oriol Vinyals
We present a deep reinforcement learning approach to minimizing the execution cost of neural network computation graphs in an optimizing compiler.