151 citations · 632 across the 84 of their papers we have counts for
87 papers
Deep graph kernel point processes over networks
Zheng Dong, Matthew Repasky, Xiuyuan Cheng +1
Point process models are widely used for continuous-time discrete-event data, where each data point includes time and additional information called "marks," such as locations, node…
Variable Selection for Kernel Two-Sample Tests
Jie Wang, Santanu S. Dey, Yao Xie
We consider the variable selection problem for two-sample tests, aiming to select the most informative variables to determine whether two collections of samples follow the same dis…
Causal Structural Learning from Time Series: A Convex Optimization Approach
Song Wei, Yao Xie
Structural learning, which aims to learn directed acyclic graphs (DAGs) from observational data, is foundational to causal reasoning and scientific discovery. Recent advancements f…
Normalizing flow neural networks by JKO scheme
Chen Xu, Xiuyuan Cheng, Yao Xie
Normalizing flow is a class of deep generative models for efficient sampling and likelihood estimation, which achieves attractive performance, particularly in high dimensions. The…
Novelty Detection for Election Fraud: A Case Study with Agent-Based Simulation Data
Khurram Yamin, Nima Jadali, Dima Nazzal +1
In this paper, we propose a robust election simulation model and independently developed election anomaly detection algorithm that demonstrates the simulation's utility. The simula…
Online Detection Of Supply Chain Network Disruptions Using Sequential Change-Point Detection for Hawkes Processes
Khurram Yamin, Haoyun Wang, Benoit Montreuil +1
In this paper, we attempt to detect an inflection or change-point resulting from the Covid-19 pandemic on supply chain data received from a large furniture company. To accomplish t…