AIRS (Artificial Intelligence Research for Science) is a collection of open-source software tools, datasets, and benchmarks associated with research work published by the DIVE Lab at Texas A&M University. Our focus here is on AI for Science, including AI for quantum and classic physics, chemistry, molecular simulation, drug discovery, material science, continuum mechanics and partial differential equations, etc. Our goal is to develop and maintain an integrated, open, reproducible, and sustainable set of resources in order to propel the emerging and rapidly growing field of AI for Science. Our current list of resources includes:
- OpenQM: Artificial Intelligence Research for Quantum Mechanics
- OpenDFT: Artificial Intelligence Research for Density Functional Theory
- OpenMol: Artificial Intelligence Research for Molecular Simulation
- OpenProt: Artificial Intelligence Research for Protein Science
- OpenMat: Artificial Intelligence Research for Material Science
- OpenMI: Artificial Intelligence Research for Molecular Interactions
- OpenPDE: Artificial Intelligence Research for Partial Differential Equations