Sharp Entrywise Perturbation Bounds for Markov Chains. - Erik H. Thiede; Brian Van Koten; Jonathan Weare (SIAM J. Matrix Anal. Appl., 2015)

The general theory of permutation equivarant neural networks and higher order graph variational encoders. - Erik Henning Thiede; Truong-Son Hy; Risi Kondor (CoRR, 2020)

A community-powered search of machine learning strategy space to find NMR property prediction models. - Lars A. Bratholm; Will Gerrard; Brandon M. Anderson; Shaojie Bai; Sunghwan Choi; Lam Dang; Pavel Hanchar; Addison Howard; Guillaume Huard; Sanghoon Kim; J. Zico Kolter; Risi Kondor; et al. (CoRR, 2020)

Stratification as a General Variance Reduction Method for Markov Chain Monte Carlo. - Aaron R. Dinner; Erik H. Thiede; Brian Van Koten; Jonathan Weare (SIAM/ASA J. Uncertain. Quantification, 2020)

Autobahn: Automorphism-based Graph Neural Nets. - Erik H. Thiede; Wenda Zhou; Risi Kondor (NeurIPS, 2021)

Error Bounds for Dynamical Spectral Estimation. - Robert J. Webber; Erik H. Thiede; Douglas Dow; Aaron R. Dinner; Jonathan Weare (SIAM J. Math. Data Sci., 2021)

Group-Equivariant Neural Networks with Fusion Diagrams. - Zimu Li; Han Zheng; Erik H. Thiede; Junyu Liu; Risi Kondor (CoRR, 2022)