88 citations · 174 across the 9 of their papers we have counts for
14 papers
Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs
Truong Son Hy, Risi Kondor
Multiresolution Matrix Factorization (MMF) is unusual amongst fast matrix factorization algorithms in that it does not make a low rank assumption. This makes MMF especially well su…
Lorentz Group Equivariant Neural Network for Particle Physics
Alexander Bogatskiy, Brandon Anderson, Jan T. Offermann +3
We present a neural network architecture that is fully equivariant with respect to transformations under the Lorentz group, a fundamental symmetry of space and time in physics. The…
The general theory of permutation equivarant neural networks and higher order graph variational encoders
Erik Henning Thiede, Truong Son Hy, Risi Kondor
Previous work on symmetric group equivariant neural networks generally only considered the case where the group acts by permuting the elements of a single vector. In this paper we…
Asymmetric Multiresolution Matrix Factorization
Pramod Kaushik Mudrakarta, Shubhendu Trivedi, Risi Kondor
Multiresolution Matrix Factorization (MMF) was recently introduced as an alternative to the dominant low-rank paradigm in order to capture structure in matrices at multiple differe…
Deep Learning for Automated Classification and Characterization of Amorphous Materials
Kirk Swanson, Shubhendu Trivedi, Joshua Lequieu +2
It is difficult to quantify structure-property relationships and to identify structural features of complex materials. The characterization of amorphous materials is especially cha…
Cormorant: Covariant Molecular Neural Networks
Brandon Anderson, Truong-Son Hy, Risi Kondor
We propose Cormorant, a rotationally covariant neural network architecture for learning the behavior and properties of complex many-body physical systems. We apply these networks t…