Randomized QR with Column Pivoting. - Jed A. Duersch; Ming Gu 002 (SIAM J. Sci. Comput., 2017)

A Robust and Efficient Implementation of LOBPCG. - Jed A. Duersch; Meiyue Shao; Chao Yang 001; Ming Gu 002 (SIAM J. Sci. Comput., 2018)

Generalizing Information to the Evolution of Rational Belief. - Jed A. Duersch; Thomas A. Catanach (Entropy, 2020)

Randomized Projection for Rank-Revealing Matrix Factorizations and Low-Rank Approximations. - Jed A. Duersch; Ming Gu 002 (SIAM Rev., 2020)

Generalized Canonical Polyadic Tensor Decomposition. - David Hong; Tamara G. Kolda; Jed A. Duersch (SIAM Rev., 2020)

Parsimonious Inference. - Jed A. Duersch; Thomas A. Catanach (CoRR, 2021)

Variational Kalman Filtering with H∞-Based Correction for Robust Bayesian Learning in High Dimensions. - Niladri Das; Jed A. Duersch; Tommie A. Catanach (CDC, 2022)

Adaptive n-ary Activation Functions for Probabilistic Boolean Logic. - Jed A. Duersch; Thomas A. Catanach; Niladri Das (CoRR, 2022)

Variational Kalman Filtering with Hinf-Based Correction for Robust Bayesian Learning in High Dimensions. - Niladri Das; Jed A. Duersch; Thomas A. Catanach (CoRR, 2022)

An Efficient Quadrature Sequence and Sparsifying Methodology for Mean-Field Variational Inference. - Jed A. Duersch (CoRR, 2023)

Curvature in the Looking-Glass: Optimal Methods to Exploit Curvature of Expectation in the Loss Landscape. - Jed A. Duersch; Tommie A. Catanach; Alexander Safonov; Jeremy Wendt (CoRR, 2024)

Logical activation functions for training arbitrary probabilistic Boolean operations. - Jed A. Duersch; Tommie A. Catanach; Niladri Das (Inf. Sci., 2024)

Projective Integral Updates for High-Dimensional Variational Inference. - Jed A. Duersch (SIAM/ASA J. Uncertain. Quantification, 2024)