3 citations · 3 across the 6 of their papers we have counts for
7 papers
Rotational Equivariance in Machine Learning: A Comprehensive Tutorial
Peter Lippmann, Fred A. Hamprecht
Rotational symmetry is one of the most important structural principles in machine learning on 3D data. In applications ranging from physics and materials science to 3D computer vis…
Equivariance by Local Canonicalization: A Matter of Representation
Gerrit Gerhartz, Peter Lippmann, Fred A. Hamprecht
Equivariant neural networks offer strong inductive biases for learning from molecular and geometric data but often rely on specialized, computationally expensive tensor operations.…
Lorentz-Equivariance without Limitations
Luigi Favaro, Gerrit Gerhartz, Fred A. Hamprecht +5
Lorentz Local Canonicalization (LLoCa) ensures exact Lorentz-equivariance for arbitrary neural networks with minimal computational overhead. For the LHC, it equivariantly predicts…
Lorentz Local Canonicalization: How to Make Any Network Lorentz-Equivariant
Jonas Spinner, Luigi Favaro, Peter Lippmann +4
Lorentz-equivariant neural networks are becoming the leading architectures for high-energy physics. Current implementations rely on specialized layers, limiting architectural choic…
Stable and Accurate Orbital-Free DFT Powered by Machine Learning
Roman Remme, Tobias Kaczun, Tim Ebert +10
Hohenberg and Kohn have proven that the electronic energy and the one-particle electron density can, in principle, be obtained by minimizing an energy functional with respect to th…
Beyond Canonicalization: How Tensorial Messages Improve Equivariant Message Passing
Peter Lippmann, Gerrit Gerhartz, Roman Remme +1
In numerous applications of geometric deep learning, the studied systems exhibit spatial symmetries and it is desirable to enforce these. For the symmetry of global rotations and r…
Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources
Peter Lippmann, Enrique Fita Sanmartín, Fred A. Hamprecht
Branched Optimal Transport (BOT) is a generalization of optimal transport in which transportation costs along an edge are subadditive. This subadditivity models an increase in tran…