Fiats: Functional inference and training for surrogates

Fortran C Submitted 02 July 2025Published 06 December 2025
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Editor: @espottesmith (all papers)
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Authors

Damian Rouson (0000-0002-2344-868X), Dan Bonachea (0000-0002-0724-9349), Brad Richardson (0000-0002-3205-2169), Jordan A. Welsman (0000-0002-2882-594X), Jeremiah Bailey (0000-0002-0436-9118), Ethan D. Gutmann (0000-0003-4077-3430), David Torres (0000-0003-2469-5284), Katherine Rasmussen (0000-0001-7974-1853), Baboucarr Dibba (0009-0008-0479-3948), Yunhao Zhang (0009-0009-3182-9296), Kareem Weaver (0009-0009-3846-6248), Zhe Bai (0000-0002-3092-0903), Tan Nguyen (0000-0003-3748-403X)

Citation

Rouson et al., (2025). Fiats: Functional inference and training for surrogates. Journal of Open Source Software, 10(116), 8785, https://doi.org/10.21105/joss.08785

@article{Rouson2025, doi = {10.21105/joss.08785}, url = {https://doi.org/10.21105/joss.08785}, year = {2025}, publisher = {The Open Journal}, volume = {10}, number = {116}, pages = {8785}, author = {Rouson, Damian and Bonachea, Dan and Richardson, Brad and Welsman, Jordan A. and Bailey, Jeremiah and Gutmann, Ethan D. and Torres, David and Rasmussen, Katherine and Dibba, Baboucarr and Zhang, Yunhao and Weaver, Kareem and Bai, Zhe and Nguyen, Tan}, title = {Fiats: Functional inference and training for surrogates}, journal = {Journal of Open Source Software} }
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artificial neural networks high-performance computing parallel programming deep learning

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