Gaussian processes

3 items, newest first.

2025
Publication
Machine Learning-Driven First-Principles Modeling of Far-Infrared Materials
Ritwik Das. PhD thesis, Université Paris-Saclay, C2N (CNRS). NNT 2025UPAST100
Physics AI/ML Bayesian optimization Gaussian processes Machine learning DFT+U Hybrid functionals GW InSb InAsSb alloys Heterointerfaces Band alignment Virtual crystal approximation Alloys Infrared materials Semiconductors
2024
Publication
BMach: a Bayesian machine for optimizing Hubbard U parameters in DFT+U with machine learning
R. Das. arXiv preprint
AI/ML Physics Bayesian optimization Gaussian processes Machine learning DFT+U
2023–2024
Project
BMach, Bayesian optimization of Hubbard U
A Bayesian framework that calibrates Hubbard U and hybrid-functional parameters at a small fraction of the cost of direct high-level methods.
AI/ML Physics Bayesian optimization Gaussian processes Machine learning DFT+U Hybrid functionals