Connectionists: Focused issue on XAI in Sciences in MLST

[Zwolak, Justyna P. (Fed)]

Dear Colleagues,

We are happy to announce that the XAI4Sci<https://xai4sci.github.io/>: Explainable Machine Learning for Sciences<https://xai4sci.github.io/> workshop has partnered with Machine Learning: Science and Technology<https://iopscience.iop.org/journal/2632-2153> journal (IOPublishing) to publish a focused issue on XAI in sciences, with Craig Greenberg of the National Institute of Standards and Technology, Rich Caruana of Microsoft Research, and myself as guest editors.

Machine Learning: Science and Technology is a multidisciplinary open-access journal that bridges the application of machine learning across the sciences with advances in machine learning methods and theory as motivated by physical insights.

The submission site opens on April 1st, 2024, and will remain open until June 30th, 2024.

Feel free to reach out to us at xai4sci2024 at gmail.com<http://xai4sci2024@gmail.com/> if you are interested in submitting your work for consideration in the focused issue or if you have any questions.

Best,
Justyna, Craig, and Rich

Applied and Computational Mathematics Division
National Institute of Standards and Technology
100 Bureau Drive, Stop 8910
Gaithersburg, MD 20899-8910 USA
Phone: (301) 975-0527
Email:  jpzwolak at nist.gov<http://jpzwolak@nist.gov/>


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