Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models. - Jayaraman J. Thiagarajan; Bindya Venkatesh; Rushil Anirudh; Peer-Timo Bremer; Jim Gaffney; Gemma Anderson; Brian K. Spears (CoRR, 2020)

Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations. - Gemma J. Anderson; Jim A. Gaffney; Brian K. Spears; Peer-Timo Bremer; Rushil Anirudh; Jayaraman J. Thiagarajan (CoRR, 2020)

Transfer learning suppresses simulation bias in predictive models built from sparse, multi-modal data. - Bogdan Kustowski; Jim A. Gaffney; Brian K. Spears; Gemma J. Anderson; Rushil Anirudh; Peer-Timo Bremer; Jayaraman J. Thiagarajan (CoRR, 2021)

The data-driven future of high-energy-density physics. - Peter W. Hatfield; Jim A. Gaffney; Gemma J. Anderson; Suzanne Ali; Luca Antonelli; Suzan Basegmez du Pree; Jonathan Citrin; Marta Fajardo; Patrick F. Knapp; Brendan Kettle; Bogdan Kustowski; Michael J. MacDonald; et al. (Nat., 2021)

Suppressing simulation bias in multi-modal data using transfer learning. - Bogdan Kustowski; Jim A. Gaffney; Brian K. Spears; Gemma J. Anderson; Rushil Anirudh; Peer-Timo Bremer; Jayaraman J. Thiagarajan; Michael K. G. Kruse; Ryan Nora (Mach. Learn. Sci. Technol., 2022)