3.1k citations · 28k across the 184 of their papers we have counts for
3 papers · 2 filters
Meta-Learning for One-Class Classification with Few Examples using Order-Equivariant Network
Ademola Oladosu, Tony Xu, Philip Ekfeldt +5
This paper presents a meta-learning framework for few-shots One-Class Classification (OCC) at test-time, a setting where labeled examples are only available for the positive class,…
Discovering Symbolic Models from Deep Learning with Inductive Biases
Miles Cranmer, Alvaro Sanchez-Gonzalez, Peter Battaglia +4
We develop a general approach to distill symbolic representations of a learned deep model by introducing strong inductive biases. We focus on Graph Neural Networks (GNNs). The tech…
Lagrangian Neural Networks
Miles Cranmer, Sam Greydanus, Stephan Hoyer +3
Accurate models of the world are built upon notions of its underlying symmetries. In physics, these symmetries correspond to conservation laws, such as for energy and momentum. Yet…