34 citations · 63 across the 8 of their papers we have counts for
3 papers · 1 filter
Warm-starting PDE solvers with any-dimensional machine learning
Wilson G. Gregory, George A. Kevrekidis, Ben Blum-Smith +1
Any-dimensional machine learning models, such as graph neural networks (GNNs), can be naturally trained and evaluated on inputs of different sizes and dimensions. Inspired by the G…
Machine learning and invariant theory
Ben Blum-Smith, Soledad Villar
Inspired by constraints from physical law, equivariant machine learning restricts the learning to a hypothesis class where all the functions are equivariant with respect to some gr…
Dimensionless machine learning: Imposing exact units equivariance
Soledad Villar, Weichi Yao, David W. Hogg +2
Units equivariance (or units covariance) is the exact symmetry that follows from the requirement that relationships among measured quantities of physics relevance must obey self-co…