Parallel Local Approximation MCMC for Expensive Models. - Patrick R. Conrad; Andrew D. Davis; Youssef M. Marzouk; Natesh S. Pillai; Aaron Smith (SIAM/ASA J. Uncertain. Quantification, 2018)

Testing a deep convolutional neural network for automated hippocampus segmentation in a longitudinal sample of healthy participants. - Nikita Nogovitsyn; Roberto Souza 001; Meghan Muller; Amelia Srajer; Stefanie Hassel; Stephen R. Arnott; Andrew D. Davis; Geoffrey B. C. Hall; Jacqueline K. Harris; Mojdeh Zamyadi; Paul D. Metzak; Zahinoor Ismail; et al. (NeuroImage, 2019)

Graph-theoretic algorithms for Kolmogorov operators: Approximating solutions and their gradients in elliptic and parabolic problems on manifolds. - Andrew D. Davis; Dimitrios Giannakis (CoRR, 2021)

MUQ: The MIT Uncertainty Quantification Library. - Matthew D. Parno; Andrew D. Davis; Linus Seelinger (J. Open Source Softw., 2021)

Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center study. - Aras Kayvanrad; Stephen R. Arnott; Nathan William Churchill; Stefanie Hassel; Aditi Chemparathy; Fan Dong; Mojdeh Zamyadi; Tom Gee; Robert Bartha; Sandra E. Black; Jane M. Lawrence-Dewar; Christopher J. M. Scott; et al. (NeuroImage, 2021)

ParticLS: Object-oriented software for discrete element methods and peridynamics. - Andrew D. Davis; Brendan A. West; Nathanael J. Frisch; Devin T. O'Connor; Matthew D. Parno (CoRR, 2022)

Rate-optimal refinement strategies for local approximation MCMC. - Andrew D. Davis; Youssef M. Marzouk; Aaron Smith; Natesh S. Pillai (Stat. Comput., 2022)

UM-Bridge: Uncertainty quantification and modeling bridge. - Linus Seelinger; Vivian Cheng-Seelinger; Andrew D. Davis; Matthew D. Parno; Anne Reinarz (J. Open Source Softw., 2023)