Category: Machine learning

Analysis software that determines 2D material structures from quantum-beam diffraction data (predecessor of ODAT-SE)

• Determine structures of surfaces and 2D materials from diffraction data

Framework for configurational sampling of multi-component disordered systems, such as metal and oxide alloys, using machine-learning models that reproduce first-principles energies

• Run configurational sampling with a model trained on first-principles energies

Optimization and inverse-problem framework for experimental data analysis (formerly 2DMAT)

• Determine structures from experimental data such as total-reflection high-energy positron diffraction
• Solve inverse problems with Bayesian optimization, replica exchange and other methods

Fast Bayesian optimization library for physics and materials science

• Speed up searches over experimental or computational candidates with Bayesian optimization

[Related library] Cython-accelerated core modules of PHYSBO (not needed from PHYSBO v3.1.0)