Classification of nodal pockets in many-electron wave functions via machine learning

DOI10.1007/s10910-012-0019-5zbMath1266.68158OpenAlexW2150428473MaRDI QIDQ445427

William A. jun. Lester, Erin LeDell, Prabhat, Dmitry Yu. Zubarev, Brian Austin

Publication date: 24 August 2012

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

Full work available at URL: https://escholarship.org/uc/item/7jf0h11f

zbMATH Keywords

quantum chemistrymachine learningbinary classificationelectronic structure theoryfixed-node diffusion Monte Carlomany-body methods

Mathematics Subject Classification ID

Measures of association (correlation, canonical correlation, etc.) (62H20) Chemistry (92E99) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• R
• caret
• SuperLearner
• ElemStatLearn

Cites Work

• Unnamed Item
• ElemStatLearn
• Many-Body Problem with Strong Forces
• Nearest neighbor pattern classification
• New Developments in Molecular Orbital Theory
• The elements of statistical learning. Data mining, inference, and prediction
• Stochastic gradient boosting.

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