From 4eeb10c994966fd75561779f92692065248f2d3b Mon Sep 17 00:00:00 2001 From: Dan Bonachea Date: Tue, 17 Mar 2026 08:41:52 -0700 Subject: [PATCH] README: Add publications and acknowledgments --- README.md | 36 +++++++++++++++++++++++++++++++++++- 1 file changed, 35 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index ce894650f..db35a5706 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,7 @@ Fiats: Functional inference and training for surrogates ======================================================= Alternatively, _Fortran inference and training for science_. -[Overview](#overview) | [Getting Started](#getting-started) | [Documentation](#documentation) +[Overview](#overview) | [Getting Started](#getting-started) | [Documentation](#documentation) | [Publications](#publications) Overview -------- @@ -209,6 +209,40 @@ Please see our [GitHub Pages site] for Hypertext Markup Languge (HTML) documenta ### UML Please see the [`doc/uml`](https://github.com/BerkeleyLab/fiats/blob/main/doc/uml) subdirectory for Unified Modeling Language (UML) diagrams such as a comprehensive Fiats [class diagram] with human-readable [Mermaid] source that renders graphically when opened by browsing to the document on GitHub. +Publications +------------ + +### Citing Fiats? Please use the following publication: + +Damian Rouson, Dan Bonachea, Brad Richardson, Jordan A. Welsman, Jeremiah Bailey, Ethan D Gutmann, David Torres, Katherine Rasmussen, Baboucarr Dibba, Yunhao Zhang, Kareem Weaver, Zhe Bai, Tan Nguyen. +"[Fiats: Functional inference and training for surrogates](https://dx.doi.org/10.21105/joss.08785)", +The Journal of Open Source Software, 10(116):8785, Dec 2025. [![DOI](https://joss.theoj.org/papers/10.21105/joss.08785/status.svg)](https://doi.org/10.21105/joss.08785) +Paper: + +### Additional Publications: + +Damian Rouson, Zhe Bai, Dan Bonachea, Baboucarr Dibba, Ethan D Gutmann, Katherine Rasmussen, David Torres, Jordan A. Welsman, Yunhao Zhang. +"[Cloud microphysics training and aerosol inference with the Fiats deep learning library](https://dx.doi.org/10.25344/S4QS3J)", +Proceedings of the [Improving Scientific Software Conference (ISS25)](https://sea.ucar.edu/iss/2025/program/), Sep 2025. +Paper: + +Damian Rouson, Zhe Bai, Dan Bonachea, Kareem Ergawy, Ethan Gutmann, Michael Klemm, Katherine Rasmussen, Brad Richardson, Sameer Shende, David Torres, Yunhao Zhang. +"[Automatically parallelizing batch inference on deep neural networks using Fiats and Fortran 2023 `do concurrent`](https://doi.org/10.25344/S4VG6T)", +Proceedings of the [Fifth International Workshop on Computational Aspects of Deep Learning (CADL)](https://sites.google.com/view/cadl2025/program), Jun 2025. +Paper: + +Acknowledgments +--------------- + +This material is based upon work supported by the U.S. Department of Energy, +Office of Science, Office of Advanced Scientific Computing Research and Office +of Nuclear Physics, Scientific Discovery through Advanced Computing (SciDAC) +Next-Generation Scientific Software Technologies (NGSST) programs under +Contract No. DE-AC02-05CH11231. This material is also based on work supported +by Laboratory Directed Research and Development (LDRD) funding from Lawrence +Berkeley National Laboratory, provided by the Director, Office of Science, of +the U.S. DOE under Contract No. DE-AC02-05CH11231. + [Building and testing]: #building-and-testing [Caffeine]: https://go.lbl.gov/caffeine [class diagram]: https://github.com/BerkeleyLab/fiats/blob/main/doc/uml/class-diagram.md