Dimensionless machine learning: Imposing exact units equivariance

Dimensionless machine learning: Imposing exact units equivariance

2 April 2022

Bianca Dumitrascu

Papers citing "Dimensionless machine learning: Imposing exact units equivariance"

10 / 10 papers shown

Title
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups Zakhar Shumaylov Peter Zaika James Rowbottom Ferdia Sherry Melanie Weber Carola-Bibiane Schönlieb 34 1 0 03 Oct 2024
Explainable Deep Learning for Tumor Dynamic Modeling and Overall Survival Prediction using Neural-ODE Mark A. Laurie James Lu 6 12 0 02 Aug 2023
Any-dimensional equivariant neural networks Eitan Levin Mateo Díaz 21 6 0 10 Jun 2023
On the Parameter Combinations That Matter and on Those That do Not N. Evangelou Noah J. Wichrowski George A. Kevrekidis Felix Dietrich M. Kooshkbaghi Sarah McFann Ioannis G. Kevrekidis 28 13 0 13 Oct 2021
A simple equivariant machine learning method for dynamics based on scalars Weichi Yao Kate Storey-Fisher D. Hogg Soledad Villar AI4CE 35 9 0 07 Oct 2021
Invariant polynomials and machine learning W. Haddadin 32 7 0 26 Apr 2021
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups Marc Finzi Max Welling A. Wilson 71 185 0 19 Apr 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 44 89 0 25 Feb 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 198 1,232 0 08 Jan 2021
Domain Adaptation: Learning Bounds and Algorithms Yishay Mansour M. Mohri Afshin Rostamizadeh 179 788 0 19 Feb 2009