Merlin: Enabling Machine Learning-Ready HPC Ensembles. - J. Luc Peterson; Rushil Anirudh; Kevin Athey; Benjamin Bay; Peer-Timo Bremer; Vic Castillo; Francesco Di Natale; David Fox; Jim A. Gaffney; David Hysom; Sam Ade Jacobs; Bhavya Kailkhura; et al. (CoRR, 2019)

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)

Enabling machine learning-ready HPC ensembles with Merlin. - J. Luc Peterson; Benjamin Bay; Joe Koning; Peter B. Robinson; Jessica Semler; Jeremy White; Rushil Anirudh; Kevin Athey; Peer-Timo Bremer; Francesco Di Natale; David Fox; Jim A. Gaffney; et al. (Future Gener. Comput. Syst., 2022)

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)

Transformer-Powered Surrogates Close the ICF Simulation-Experiment Gap with Extremely Limited Data. - Matthew L. Olson; Shusen Liu 001; Jayaraman J. Thiagarajan; Bogdan Kustowski; Weng-Keen Wong; Rushil Anirudh (CoRR, 2023)