A probabilistic deep learning approach to automate the interpretation of multi-phase diffraction spectra. - Nathan J. Szymanski; Christopher J. Bartel; Yan Zeng; Qingsong Tu; Gerbrand Ceder (CoRR, 2021)

A universal synthetic dataset for machine learning on spectroscopic data. - Jan Schuetzke; Nathan J. Szymanski; Markus Reischl (CoRR, 2022)

AlabOS: A Python-based Reconfigurable Workflow Management Framework for Autonomous Laboratories. - Yuxing Fei; Bernardus Rendy; Rishi Kumar; Olympia Dartsi; Hrushikesh P. Sahasrabuddhe; Matthew J. McDermott; Zheren Wang; Nathan J. Szymanski; Lauren N. Walters; David Milsted; Yan Zeng; Anubhav Jain 001; et al. (CoRR, 2024)

Establishing baselines for generative discovery of inorganic crystals. - Nathan J. Szymanski; Christopher J. Bartel (CoRR, 2025)