mad-GP: automatic differentiation of Gaussian processes for molecules and materials

DOI10.1007/s10910-022-01334-xzbMath1491.92142OpenAlexW4221033215MaRDI QIDQ2141365

Yanyan Li

Publication date: 25 May 2022

Published in: Journal of Mathematical Chemistry (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10910-022-01334-x

Mathematics Subject Classification ID

Gaussian processes (60G15) Molecular structure (graph-theoretic methods, methods of differential topology, etc.) (92E10)

Related Items (2)

Surrogate modeling of the effective elastic properties of spherical particle-reinforced composite materials ⋮ mad-GP

Uses Software

• SciPy
• POTLIB
• Python
• DiffSharp
• GitHub
• SchNetPack
• ASE
• DScribe
• JAX
• Cormorant
• PhysNet
• SchNet
• MULTIMODE

Cites Work

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• POTLIB 2001: A potential energy surface library for chemical systems
• Estimating 3-D location parameters using dual number quaternions
• Efficient implementation of high dimensional model representations

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