154 citations · 368 across the 11 of their papers we have counts for
13 papers
Fourier series for singular measures in higher dimensions
Chad Berner, John E. Herr, Palle E. T. Jorgensen +1
For multi-variable finite measure spaces, we present in this paper a new framework for non-orthogonal Fourier expansions. Our results hold for probability measures with f…
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials
Peter Eastman, Pavan Kumar Behara, David L. Dotson +9
Machine learning potentials are an important tool for molecular simulation, but their development is held back by a shortage of high quality datasets to train them on. We describe…
Few-Shot Graph Learning for Molecular Property Prediction
Zhichun Guo, Chuxu Zhang, Wenhao Yu +4
The recent success of graph neural networks has significantly boosted molecular property prediction, advancing activities such as drug discovery. The existing deep neural network m…
Identifying Complex Hadamard Submatrices of the Fourier Matrices via Primitive Sets
John E. Herr, Troy M. Wiegand
For a given selection of rows and columns from a Fourier matrix, we give a number of tests for whether the resulting submatrix is Hadamard based on the primitive sets of those rows…
Compressing physical properties of atomic species for improving predictive chemistry
John E. Herr, Kevin Koh, Kun Yao +1
The answers to many unsolved problems lie in the intractable chemical space of molecules and materials. Machine learning techniques are rapidly growing in popularity as a way to co…
A Characterization of Boundary Representations of Positive Matrices in the Hardy Space via the Abel Product
John E. Herr, Palle E. T. Jorgensen, Eric S. Weber
Spectral measures give rise to a natural harmonic analysis on the unit disc via a boundary representation of a positive matrix arising from a spectrum of the measure. We consider i…