activity
20122024
most citedUnsupervised Deep Haar Scattering on Graphs

20 citations · 38 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ML2024

Training Guarantees of Neural Network Classification Two-Sample Tests by Kernel Analysis

Varun Khurana, Xiuyuan Cheng, Alexander Cloninger

We construct and analyze a neural network two-sample test to determine whether two datasets came from the same distribution (null hypothesis) or not (alternative hypothesis). We pe…

stat.ML20231 cited

Neural Differential Recurrent Neural Network with Adaptive Time Steps

Yixuan Tan, Liyan Xie, Xiuyuan Cheng

The neural Ordinary Differential Equation (ODE) model has shown success in learning complex continuous-time processes from observations on discrete time stamps. In this work, we co…

math.SP201612 cited

On the Diffusion Geometry of Graph Laplacians and Applications

Xiuyuan Cheng, Manas Rachh, Stefan Steinerberger

We study directed, weighted graphs and consider the (not necessarily symmetric) averaging operator whe…

cs.LG201420 cited

Unsupervised Deep Haar Scattering on Graphs

Xu Chen, Xiuyuan Cheng, Stéphane Mallat

The classification of high-dimensional data defined on graphs is particularly difficult when the graph geometry is unknown. We introduce a Haar scattering transform on graphs, whic…

math.PR20125 cited

The Spectrum of Random Inner-product Kernel Matrices

Xiuyuan Cheng, Amit Singer

We consider n-by-n matrices whose (i, j)-th entry is f(X_i^T X_j), where X_1, ...,X_n are i.i.d. standard Gaussian random vectors in R^p, and f is a real-valued function. The eigen…