We describe a discrete Laplacian suitable for any triangle mesh, including those that are
nonmanifold or nonorientable (with or without boundary). Our Laplacian is a robust drop‐in …

In this paper, we propose an improvement of an algorithm of Aurenhammer, Hoffmann and
Aronov to find a least square matching between a probability density and finite set of sites …

We present a fast, scalable algorithm to generate high-quality blue noise point distributions
of arbitrary density functions. At its core is a novel formulation of the recently-introduced …

An introduction to geometry processing using discrete exterior calculus (DEC), which
provides a simple, flexible, and efficient framework for building a unified geometry …

We introduce a novel method for computing the earth mover's distance (EMD) between
probability distributions on a discrete surface. Rather than using a large linear program with …

This paper introduces a new particle-based approach to incompressible fluid simulation. We
depart from previous Lagrangian methods by considering fluid particles no longer purely as …

These notes focus on three-dimensional geometry processing, while simultaneously
providing a first course in traditional differential geometry. Our main goal is to show how …

Triangle meshes remain the most popular data representation for surface geometry. This
ubiquitous representation is essentially a hybrid one that decouples continuous vertex …

We propose a robust 2D shape reconstruction and simplification algorithm which takes as
input a defect‐laden point set with noise and outliers. We introduce an optimal‐transport …

We apply the tensor train (TT) decomposition to construct the tensor product polynomial
chaos expansion (PCE) of a random field, to solve the stochastic elliptic diffusion PDE with …