Finding latent structures in data is drawing increasing attention in diverse fields such as
image and signal processing, fluid dynamics, and machine learning. In this work we …

Two key ideas have greatly improved techniques for image enhancement and denoising:
the lifting of image data to multi-orientation distributions and the application of nonlinear …

In this work we develop a nonlinear decomposition, associated with nonlinear
eigenfunctions of the p-Laplacian for p∈(1, 2). With this decomposition we can process …

Local M-smoothers are interesting and important signal and image processing techniques
with many connections to other methods. In our paper, we derive a family of partial …

Extracting the latent underlying structures of complex nonlinear local and nonlocal flows is
essential for their analysis and modeling. In this Element the authors attempt to provide a …

We investigate the behavior of the numerical solutions of the p-Laplacian Allen–Cahn
equation. Because of the p-Laplacian's challenging numerical properties, many different …

Finding latent structures in data is drawing increasing attention in diverse fields such as fluid
dynamics, signal processing, and machine learning. Dimensionality reduction facilitates the …