Nathan J. Szymanski

According to our database, Nathan J. Szymanski authored at least 5 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Thermodynamic assessment of machine learning models for solid-state synthesis prediction.

Jane Schlesinger, Simon Hjaltason, Nathan J. Szymanski, Christopher J. Bartel

CoRR, February, 2026

2025

Establishing baselines for generative discovery of inorganic crystals.

Nathan J. Szymanski, Christopher J. Bartel

CoRR, January, 2025

2024

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, Gerbrand Ceder

CoRR, 2024

2022

A universal synthetic dataset for machine learning on spectroscopic data.

Jan Schuetzke, Nathan J. Szymanski, Markus Reischl

CoRR, 2022

2021

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