
DoublyStochastic Normalization of the Gaussian Kernel is Robust to Heteroskedastic Noise
A fundamental step in many dataanalysis techniques is the construction ...
read it

LOCA: LOcal Conformal Autoencoder for standardized data coordinates
We propose a deeplearning based method for obtaining standardized data ...
read it

Comanifold learning with missing data
Representation learning is typically applied to only one mode of a data ...
read it

Manifold learning with bistochastic kernels
In this paper we answer the following question: what is the infinitesima...
read it

Twosample Statistics Based on Anisotropic Kernels
The paper introduces a new kernelbased Maximum Mean Discrepancy (MMD) s...
read it

DataDriven Tree Transforms and Metrics
We consider the analysis of high dimensional data given in the form of a...
read it

Hierarchical Coupled Geometry Analysis for Neuronal Structure and Activity Pattern Discovery
In the wake of recent advances in experimental methods in neuroscience, ...
read it

Provable approximation properties for deep neural networks
We discuss approximation of functions using deep neural nets. Given a fu...
read it

Bigeometric Organization of Deep Nets
In this paper, we build an organization of highdimensional datasets tha...
read it
Ronald R. Coifman
is this you? claim profile
Professor of Math and Computer Science at Yale University