2 citations · 2 across the 4 of their papers we have counts for
10 papers
On Complex Analytic tools, and the Holomorphic Rotation methods
Ronald R. Coifman, Jacques Peyrière, Guido Weiss
We describe recent nonlinear analytic approximation tools in the classical setting of Hardy spaces in the upper half plane and show how to transfer them to the higher dimensional r…
Questionnaires to PDEs: From Disorganized Data to Emergent Generative Dynamic Models
David W. Sroczynski, Felix P. Kemeth, Ronald R. Coifman +1
Starting with sets of disorganized observations of spatially varying and temporally evolving systems, obtained at different (also disorganized) sets of parameters, we demonstrate t…
Diffusion Earth Mover's Distance and Distribution Embeddings
Alexander Tong, Guillaume Huguet, Amine Natik +5
We propose a new fast method of measuring distances between large numbers of related high dimensional datasets called the Diffusion Earth Mover's Distance (EMD). We model the datas…
Multiscale decompositions of Hardy spaces
Ronald R. Coifman, Jacques Peyrière
An inspiration at the origin of wavelet analysis (when Grossmann, Morlet, Meyer and collaborators were interacting and exploring versions of multiscale representations) was provide…
Doubly-Stochastic Normalization of the Gaussian Kernel is Robust to Heteroskedastic Noise
Boris Landa, Ronald R. Coifman, Yuval Kluger
A fundamental step in many data-analysis techniques is the construction of an affinity matrix describing similarities between data points. When the data points reside in Euclidean…
Co-manifold learning with missing data
Gal Mishne, Eric C. Chi, Ronald R. Coifman
Representation learning is typically applied to only one mode of a data matrix, either its rows or columns. Yet in many applications, there is an underlying geometry to both the ro…