activity
20102025
most citedA Survey of Information Cascade Analysis: Models, Predictions, and Recent Advances

225 citations · 446 across the 13 of their papers we have counts for

collaborators

13 papers

cs.AI2025

Root Cause Analysis of Hydrogen Bond Separation in Spatio-Temporal Molecular Dynamics using Causal Models

Rahmat K. Adesunkanmi, Ashfaq Khokhar, Goce Trajcevski +1

Molecular dynamics simulations (MDS) face challenges, including resource-heavy computations and the need to manually scan outputs to detect "interesting events," such as the format…

cs.LG2024★ 5 cited

Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-Level Anomaly Detection

Chunjing Xiao, Shikang Pang, Wenxin Tai +3

Graph-level anomaly detection is significant in diverse domains. To improve detection performance, counterfactual graphs have been exploited to benefit the generalization capacity…

cs.LG2024

Counterfactual Data Augmentation with Denoising Diffusion for Graph Anomaly Detection

Chunjing Xiao, Shikang Pang, Xovee Xu +3

A critical aspect of Graph Neural Networks (GNNs) is to enhance the node representations by aggregating node neighborhood information. However, when detecting anomalies, the repres…

cs.DB2023★ 1 cited

A Universal Scheme for Dynamic Partitioned Shortest Path Index: Survey, Improvement, and Experiments

Mengxuan Zhang, Xinjie Zhou, Lei Li +4

Shortest Path (SP) computation is a fundamental operation in many real-life applications such as navigation on road networks, link analysis on social networks, etc. These networks…

cs.OH2023★ 4 cited

Towards Mobility Data Science (Vision Paper)

Mohamed Mokbel, Mahmoud Sakr, Li Xiong +45

Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of GPS-equipped mobile devices and other inexpensive location-tracki…

cs.LG2022

Predicting Human Mobility via Self-supervised Disentanglement Learning

Qiang Gao, Jinyu Hong, Xovee Xu +3

Deep neural networks have recently achieved considerable improvements in learning human behavioral patterns and individual preferences from massive spatial-temporal trajectories da…