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Dive into the research topics where James H. von Brecht is active.

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Featured researches published by James H. von Brecht.


Journal of Computational Physics | 2010

A second order virtual node method for elliptic problems with interfaces and irregular domains

Jacob Bedrossian; James H. von Brecht; Siwei Zhu; Eftychios Sifakis; Joseph Teran

We present a second order accurate, geometrically flexible and easy to implement method for solving the variable coefficient Poisson equation with interfacial discontinuities or on irregular domains, handling both cases with the same approach. We discretize the equations using an embedded approach on a uniform Cartesian grid employing virtual nodes at interfaces and boundaries. A variational method is used to define numerical stencils near these special virtual nodes and a Lagrange multiplier approach is used to enforce jump conditions and Dirichlet boundary conditions. Our combination of these two aspects yields a symmetric positive definite discretization. In the general case, we obtain the standard 5-point stencil away from the interface. For the specific case of interface problems with continuous coefficients, we present a discontinuity removal technique that admits use of the standard 5-point finite difference stencil everywhere in the domain. Numerical experiments indicate second order accuracy in L^~.


Mathematical Models and Methods in Applied Sciences | 2012

PREDICTING PATTERN FORMATION IN PARTICLE INTERACTIONS

James H. von Brecht; David Uminsky; Theodore Kolokolnikov

Large systems of particles interacting pairwise in d dimensions give rise to extraordinarily rich patterns. These patterns generally occur in two types. On one hand, the particles may concentrate on a co-dimension one manifold such as a sphere (in 3D) or a ring (in 2D). Localized, space-filling, co-dimension zero patterns can occur as well. In this paper, we utilize a dynamical systems approach to predict such behaviors in a given system of particles. More specifically, we develop a nonlocal linear stability analysis for particles uniformly distributed on a d - 1 sphere. Remarkably, the linear theory accurately characterizes the patterns in the ground states from the instabilities in the pairwise potential. This aspect of the theory then allows us to address the issue of inverse statistical mechanics in self-assembly: given a ground state exhibiting certain instabilities, we construct a potential that corresponds to such a pattern.


neural information processing systems | 2013

Multiclass Total Variation Clustering

Xavier Bresson; Thomas Laurent; David Uminsky; James H. von Brecht


Journal of Nonlinear Science | 2012

On Soccer Balls and Linearized Inverse Statistical Mechanics

James H. von Brecht; David Uminsky


neural information processing systems | 2012

Convergence and Energy Landscape for Cheeger Cut Clustering

Xavier Bresson; Thomas Laurent; David Uminsky; James H. von Brecht


Journal of Statistical Physics | 2013

Swarming on Random Graphs

James H. von Brecht; Theodore Kolokolnikov; Andrea L. Bertozzi; Hui Sun


Archive | 2009

A Second Order Virtual Node Method for Poisson Interface Problems on Irregular Domains

Jacob Bedrossian; James H. von Brecht; Siwei Zhu; Eftychios Sifakis; Joseph Teran


Communications in Mathematical Physics | 2013

Well-Posedness Theory for Aggregation Sheets

James H. von Brecht; Andrea L. Bertozzi


arXiv: Optimization and Control | 2013

An Adaptive Total Variation Algorithm for Computing the Balanced Cut of a Graph

Xavier Bresson; Thomas Laurent; David Uminsky; James H. von Brecht


arXiv: Machine Learning | 2014

An Incremental Reseeding Strategy for Clustering

Xavier Bresson; Huiyi Hu; Thomas Laurent; Arthur Szlam; James H. von Brecht

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David Uminsky

University of San Francisco

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Thomas Laurent

Loyola Marymount University

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Xavier Bresson

École Polytechnique Fédérale de Lausanne

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Arthur Szlam

City College of New York

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Eftychios Sifakis

University of Wisconsin-Madison

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Joseph Teran

University of California

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Siwei Zhu

University of California

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Hui Sun

University of California

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