Title	Statistical inference on persistent homology of density filtration on Rips complex
Creator	Kim, Jisu
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2017-05-11T11:15
Description	The statistical inference on persistent homology incurs computation on a grid of points, which is computationally infeasible if the dimension is high. This work tries to mitigate computations by building a valid confidence set for the persistent homology of a density filtration on Rips complex.
Extent	10 minutes
Subject	Mathematics; Biology and other natural sciences; Algebraic topology; Mathematical biology
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: Carnegie Mellon University
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2017-11-08
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0357474
URI	http://hdl.handle.net/2429/63563
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Graduate
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

Open Collections

BIRS Workshop Lecture Videos