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UID:c2sUTAhImug8XA9cey4C5
SUMMARY:Nonparametric Bayesian Inference - Computational Issues 
DTSTAMP:20260401T014400Z
DTSTART;VALUE=DATE:20260112
DTEND;VALUE=DATE:20260116
DESCRIPTION:This program bring together researchers working in Bayesian non
	parametric inference (BNP)\, including computation\, foundations\, methodo
	logy and application of BNP methods\, with the goal of identifying newly e
	merging computational strategies and inference approaches. The program and
	 invited talks are planned to balance theoretical expertise\, interest and
	 prowess in computational methods\, and exposure to selected substantial a
	pplication areas. The intended nature of the program as identifying synerg
	ies of different approaches and potentially new research directions natura
	lly leads to favoring breath over depth\, with more emphasis on covering d
	iverse areas rather than on in-depth discussions of a single specific them
	e.
URL:https://icerm.brown.edu/program/topical_workshop/tw-26-bnp
LOCATION:Institute for Computational and Experimental Research in Mathemati
	cs\, Brown University 
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