534 citations · 2k across the 96 of their papers we have counts for
6 papers · 1 filter
Geometric Scattering on Measure Spaces
Joyce Chew, Matthew Hirn, Smita Krishnaswamy +5
The scattering transform is a multilayered, wavelet-based transform initially introduced as a model of convolutional neural networks (CNNs) that has played a foundational role in o…
An iterative warping and clustering algorithm to estimate multiple wave-shape functions from a nonstationary oscillatory signal
Marcelo A. Colominas, Hau-Tieng Wu
Nonsinusoidal oscillatory signals are everywhere. In practice, the nonsinusoidal oscillatory pattern, modeled as a 1-periodic wave-shape function (WSF), might vary from cycle to cy…
Data-Driven optimal shrinkage of singular values under high-dimensional noise with separable covariance structure with application
Pei-Chun Su, Hau-Tieng Wu
We develop a data-driven optimal shrinkage algorithm for matrix denoising in the presence of high-dimensional noise with a separable covariance structure; that is, the noise is col…
The Manifold Scattering Transform for High-Dimensional Point Cloud Data
Joyce Chew, Holly R. Steach, Siddharth Viswanath +5
The manifold scattering transform is a deep feature extractor for data defined on a Riemannian manifold. It is one of the first examples of extending convolutional neural network-l…
Application of de-shape synchrosqueezing to estimate gait cadence from a single-sensor accelerometer placed in different body locations
Hau-Tieng Wu, Jacek Urbanek
Objective: Commercial and research-grade wearable devices have become increasingly popular over the past decade. Information extracted from devices using accelerometers is frequent…
Spatiotemporal Analysis Using Riemannian Composition of Diffusion Operators
Tal Shnitzer, Hau-Tieng Wu, Ronen Talmon
Multivariate time-series have become abundant in recent years, as many data-acquisition systems record information through multiple sensors simultaneously. In this paper, we assume…