3 citations · 3 across the 1 of their papers we have counts for
3 papers
cs.CG2021★ 3 cited
Reviews: Topological Distances and Losses for Brain Networks
Moo K. Chung, Alexander Smith, Gary Shiu
Almost all statistical and machine learning methods in analyzing brain networks rely on distances and loss functions, which are mostly Euclidean or matrix norms. The Euclidean or m…
math.AT2020
Topological Data Analysis: Concepts, Computation, and Applications in Chemical Engineering
Alexander D. Smith, Pawel Dlotko, Victor M. Zavala
A primary hypothesis that drives scientific and engineering studies is that data has structure. The dominant paradigms for describing such structure are statistics (e.g., moments,…
eess.SY2020
On the Convergence of the Dynamic Inner PCA Algorithm
Sungho Shin, Alex D. Smith, S. Joe Qin +1
Dynamic inner principal component analysis (DiPCA) is a powerful method for the analysis of time-dependent multivariate data. DiPCA extracts dynamic latent variables that capture t…