682 citations · 1.3k across the 12 of their papers we have counts for
12 papers
Equilibrium Aggregation: Encoding Sets via Optimization
Sergey Bartunov, Fabian B. Fuchs, Timothy Lillicrap
Processing sets or other unordered, potentially variable-sized inputs in neural networks is usually handled by aggregating a number of input tensors into a single representation. W…
Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs
Nicolas Sonnerat, Pengming Wang, Ira Ktena +2
Large Neighborhood Search (LNS) is a combinatorial optimization heuristic that starts with an assignment of values for the variables to be optimized, and iteratively improves it by…
Computer-Aided Design as Language
Yaroslav Ganin, Sergey Bartunov, Yujia Li +2
Computer-Aided Design (CAD) applications are used in manufacturing to model everything from coffee mugs to sports cars. These programs are complex and require years of training and…
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.…
Meta-Learning Deep Energy-Based Memory Models
Sergey Bartunov, Jack W Rae, Simon Osindero +1
We study the problem of learning associative memory -- a system which is able to retrieve a remembered pattern based on its distorted or incomplete version. Attractor networks prov…
Meta-Learning Neural Bloom Filters
Jack W Rae, Sergey Bartunov, Timothy P Lillicrap
There has been a recent trend in training neural networks to replace data structures that have been crafted by hand, with an aim for faster execution, better accuracy, or greater c…