14.1k citations · 17.1k across the 31 of their papers we have counts for
3 papers · 1 filter
Pointer Graph Networks
Petar Veličković, Lars Buesing, Matthew C. Overlan +3
Graph neural networks (GNNs) are typically applied to static graphs that are assumed to be known upfront. This static input structure is often informed purely by insight of the mac…
Memory-based Parameter Adaptation
Pablo Sprechmann, Siddhant M. Jayakumar, Jack W. Rae +7
Deep neural networks have excelled on a wide range of problems, from vision to language and game playing. Neural networks very gradually incorporate information into weights as the…
Distilling the Knowledge in a Neural Network
Geoffrey Hinton, Oriol Vinyals, Jeff Dean
A very simple way to improve the performance of almost any machine learning algorithm is to train many different models on the same data and then to average their predictions. Unfo…