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SUMMARY:Electronic Structure Reading Group: Gaussian Process Regression fo
 r Materials and Molecules
DTSTART:20250203T160000
DTEND:20250203T173000
DTSTAMP:20260921T175601Z
UID:95d8199aae73ba9fd21ac11803694baf11a091158434e0845f87e4bf
CATEGORIES:Conferences - Seminars
DESCRIPTION:Anna Paulish\nIn this talk\, I will introduce the fundamentals
  of Gaussian process regression\, covering key concepts. I will discuss sp
 arse GPR techniques for efficiently handling large datasets\, such as the 
 Nyström method and subset of regressors\, as well as its application to m
 aterials modeling problems.\nReferences:\n\n	Rasmussen\, C. E.\, & William
 s\, C. K. I. (2006). Gaussian Processes for Machine Learning. The MIT Pres
 s.\n	Deringer\, V. L.\, Bartók\, A. P.\, Bernstein\, N.\, Wilkins\, D. M.
 \, Ceriotti\, M.\, & Csányi\, G. (2021). Gaussian Process Regression for 
 Materials and Molecules. Chemical Reviews\, 121(16)\, 10073–10141. http
 s://pubs.acs.org/doi/pdf/10.1021/acs.chemrev.1c00022\n\n---\nThe electroni
 c structure reading group brings together researchers and students interes
 ted in mathematical aspects of electronic structure problems and adjacent 
 topics\, including:\n\n	Density Functional Theory\n	Many-body Schrödinger
  equation for electrons\n	Born-Oppenheimer Molecular Dynamics\n	Numerical 
 analysis and error control\n\nFor updates\, join the matrix chat room at 
 #electronic-structure:epfl.ch (requires a GASPAR account).\n\nWebsite: h
 ttps://matmat.org/readinggroup/\n 
LOCATION:MA B1 524 https://plan.epfl.ch/?room==MA%20B1%20524
STATUS:CONFIRMED
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