activity
20222024
most citedTowards Better Evaluation for Dynamic Link Prediction

31 citations · 34 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SI2024

Temporal Graph Analysis with TGX

Razieh Shirzadkhani, Shenyang Huang, Elahe Kooshafar +2

Real-world networks, with their evolving relations, are best captured as temporal graphs. However, existing software libraries are largely designed for static graphs where the dyna…

cs.LG20231 cited

Towards Temporal Edge Regression: A Case Study on Agriculture Trade Between Nations

Lekang Jiang, Caiqi Zhang, Farimah Poursafaei +1

Recently, Graph Neural Networks (GNNs) have shown promising performance in tasks on dynamic graphs such as node classification, link prediction and graph regression. However, few w…

cs.LG2023

Fast and Attributed Change Detection on Dynamic Graphs with Density of States

Shenyang Huang, Jacob Danovitch, Guillaume Rabusseau +1

How can we detect traffic disturbances from international flight transportation logs or changes to collaboration dynamics in academic networks? These problems can be formulated as…

cs.LG2023

Laplacian Change Point Detection for Single and Multi-view Dynamic Graphs

Shenyang Huang, Samy Coulombe, Yasmeen Hitti +2

Dynamic graphs are rich data structures that are used to model complex relationships between entities over time. In particular, anomaly detection in temporal graphs is crucial for…

cs.LG20232 cited

GPS++: Reviving the Art of Message Passing for Molecular Property Prediction

Dominic Masters, Josef Dean, Kerstin Klaser +9

We present GPS++, a hybrid Message Passing Neural Network / Graph Transformer model for molecular property prediction. Our model integrates a well-tuned local message passing compo…

cs.LG202231 cited

Towards Better Evaluation for Dynamic Link Prediction

Farimah Poursafaei, Shenyang Huang, Kellin Pelrine +1

Despite the prevalence of recent success in learning from static graphs, learning from time-evolving graphs remains an open challenge. In this work, we design new, more stringent e…