Posts by Collection

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Comparing Shallow and Deep Graph Models for Brain Network Analysis

Published in IEEE Big Data, 2022

We benchmark the classification performance of graph kernel SVM and GNNs on neuroimaging data.

Dynamical importance and network perturbations

Published in Physical Review E, 2024

The spectral information of the adjacency matrix offers a useful notion of edge importance.

Comparing Graph Kernels and Graph Neural Networks for Brain Disease Classification

Published: July 01, 2022

Shallow vs. Deep Brain Network Models for Disease Classification

Published: July 20, 2022

Comparing Shallow and Deep Graph Models for Brain Network Analysis

Published: December 18, 2022

The Spectral Structure of One-Step Feature Learning from Spiked Data in Neural Networks

Published: September 23, 2026

Introduction to Probability

Undergraduate course, UCLA, 2026

Covers probability distributions, random variables, vectors, and expectation.