Sampling from (truncated) high-dimensional logconcave densities with VolEsti (GeomScale Project)

Short talk

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This talk focuses on sampling from (truncated) high-dimensional log-concave densities. We present the most recent contributions to VolEsti which include algorithms for log-concave sampling via efficiently solving ODEs, in the R language.


Marios Papachristou

Marios is a first-year Ph.D. student at the Computer and Information Science Department at Cornell University. He has received his undergraduate degree from the Electrical and Computer Engineering School at the National Technical University of Athens.