Gaussian Process Regression for Materials and Molecules
We provide an introduction to Gaussian process regression (GPR) machine-learning methods in computational materials science and chemistry. The focus of the present review is on ...
Publications
3 shownStructure of a large social network
We study a social network consisting of over 10(4) individuals, with a degree distribution exhibiting two power scaling regimes separated by a critical degree k(crit), and a pow...
How accurate are DFT forces? Unexpectedly large uncertainties in molecular datasets
Training of general-purpose machine learning interatomic potentials (MLIPs) relies on large datasets with properties usually computed with density functional theory (DFT). A pre...
Frequent Co-Authors
Researcher Info
- h-index
- 2
- Publications
- 3
- Citations
- 1,166
- Institution
- University of Cambridge
External Links
Identifiers
- ORCID
- 0000-0002-8180-2034
Impact Metrics
h-index
2
h-index: Number of publications with at least h citations each.