116 citations · 209 across the 16 of their papers we have counts for
16 papers
Wasserstein Archetypal Analysis
Katy Craig, Braxton Osting, Dong Wang +1
Archetypal analysis is an unsupervised machine learning method that summarizes data using a convex polytope. In its original formulation, for fixed k, the method finds a convex pol…
A two-stage method for reconstruction of parameters in diffusion equations
Xuesong Bai, Elena Cherkaev, Dong Wang
Parameter reconstruction for diffusion equations has a wide range of applications. In this paper, we proposed a two-stage scheme to efficiently solve conductivity reconstruction pr…
A modularized algorithmic framework for interface related optimization problems using characteristic functions
Dong Wang, Shangzhi Zeng, Jin Zhang
In this paper, we consider the algorithms and convergence for a general optimization problem, which has a wide range of applications in image segmentation, topology optimization, f…
Variational methods and deep Ritz method for active elastic solids
Haiqin Wang, Boyi Zou, Jian Su +2
Variational methods have been widely used in soft matter physics for both static and dynamic problems. These methods are mostly based on two variational principles: the variational…
An efficient unconditionally stable method for Dirichlet partitions in arbitrary domains
Dong Wang
A Dirichlet -partition of a domain is a collection of pairwise disjoint open subsets such that the sum of their first Laplace--Dirichlet eigenvalues is minimal. In this pape…
Probabilistic methods for approximate archetypal analysis
Ruijian Han, Braxton Osting, Dong Wang +1
Archetypal analysis is an unsupervised learning method for exploratory data analysis. One major challenge that limits the applicability of archetypal analysis in practice is the in…