Comparison of polynomial approximations to speed up planewave-based quantum Monte Carlo calculations. - William D. Parker; C. J. Umrigar; Dario Alfè; F. R. Petruzielo; Richard G. Hennig; John W. Wilkins (J. Comput. Phys., 2015)

Accelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function. - Jason B. Gibson; Ajinkya C. Hire; Philip M. Dee; Oscar Barrera; Benjamin Geisler; Peter J. Hirschfeld; Richard G. Hennig (CoRR, 2024)

When More Data Hurts: Optimizing Data Coverage While Mitigating Diversity Induced Underfitting in an Ultra-Fast Machine-Learned Potential. - Jason B. Gibson; Tesia D. Janicki; Ajinkya C. Hire; Chris Bishop; J. Matthew D. Lane; Richard G. Hennig (CoRR, 2024)

Open Materials Generation with Stochastic Interpolants. - Philipp Höllmer; Thomas Egg; Maya M. Martirossyan; Eric Fuemmeler; Amit Gupta; Zeren Shui; Pawan Prakash; Adrian Roitberg; Mingjie Liu; George Karypis; Mark K. Transtrum; Richard G. Hennig; et al. (CoRR, 2025)