19 citations · 19 across the 3 of their papers we have counts for
7 papers
Solving MaxSAT with Matrix Multiplication
David Warde-Farley, Vinod Nair, Yujia Li +3
We propose an incomplete algorithm for Maximum Satisfiability (MaxSAT) specifically designed to run on neural network accelerators such as GPUs and TPUs. Given a MaxSAT problem ins…
Competition-Level Code Generation with AlphaCode
Yujia Li, David Choi, Junyoung Chung +23
Programming is a powerful and ubiquitous problem-solving tool. Developing systems that can assist programmers or even generate programs independently could make programming more pr…
Perceiver: General Perception with Iterative Attention
Andrew Jaegle, Felix Gimeno, Andrew Brock +3
Biological systems perceive the world by simultaneously processing high-dimensional inputs from modalities as diverse as vision, audition, touch, proprioception, etc. The perceptio…
Solving Mixed Integer Programs Using Neural Networks
Vinod Nair, Sergey Bartunov, Felix Gimeno +16
Mixed Integer Programming (MIP) solvers rely on an array of sophisticated heuristics developed with decades of research to solve large-scale MIP instances encountered in practice.…
Strong Generalization and Efficiency in Neural Programs
Yujia Li, Felix Gimeno, Pushmeet Kohli +1
We study the problem of learning efficient algorithms that strongly generalize in the framework of neural program induction. By carefully designing the input / output interfaces of…
Prioritized Unit Propagation with Periodic Resetting is (Almost) All You Need for Random SAT Solving
Xujie Si, Yujia Li, Vinod Nair +1
We propose prioritized unit propagation with periodic resetting, which is a simple but surprisingly effective algorithm for solving random SAT instances that are meant to be hard.…