90 citations · 205 across the 12 of their papers we have counts for
13 papers
Interactive Extraction of High-Frequency Aesthetically-Coherent Colormaps
Santiago V. Lombeyda, Mathieu Desbrun
Color transfer functions (i.e. colormaps) exhibiting a high frequency luminosity component have proven to be useful in the visualization of data where feature detection or iso-cont…
A Discrete Exterior Calculus of Bundle-valued Forms
Theo Braune, Yiying Tong, François Gay-Balmaz +1
The discretization of Cartan's exterior calculus of differential forms has been fruitful in a variety of theoretical and practical endeavors: from computational electromagnetics to…
Dynamic Upsampling of Smoke through Dictionary-based Learning
Kai Bai, Wei Li, Mathieu Desbrun +1
Simulating turbulent smoke flows is computationally intensive due to their intrinsic multiscale behavior, thus requiring relatively high resolution grids to fully capture their com…
Parallel Transport Unfolding: A Connection-based Manifold Learning Approach
Max Budninskiy, Glorian Yin, Leman Feng +2
Manifold learning offers nonlinear dimensionality reduction of high-dimensional datasets. In this paper, we bring geometry processing to bear on manifold learning by introducing a…
Variational Partitioned Runge-Kutta methods for Lagrangians linear in velocities
Tomasz M. Tyranowski, Mathieu Desbrun
In this paper we construct higher-order variational integrators for a class of degenerate systems described by Lagrangians that are linear in velocities. We analyze the geometry un…
R-adaptive multisymplectic and variational integrators
Tomasz M. Tyranowski, Mathieu Desbrun
Moving mesh methods (also called r-adaptive methods) are space-adaptive strategies used for the numerical simulation of time-dependent partial differential equations. These methods…