Publications
- Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
- Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis
- Atomate: A high-level interface to generate, execute, and analyze computational materials science workflows
- Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
- A universal graph deep learning interatomic potential for the periodic table
- Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
- Robust training of machine learning interatomic potentials with dimensionality reduction and stratified sampling