31 citations · 58 across the 5 of their papers we have counts for
5 papers
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…
Temporal Graph Benchmark for Machine Learning on Temporal Graphs
Shenyang Huang, Farimah Poursafaei, Jacob Danovitch +7
We present the Temporal Graph Benchmark (TGB), a collection of challenging and diverse benchmark datasets for realistic, reproducible, and robust evaluation of machine learning mod…
Towards Improved Illicit Node Detection with Positive-Unlabelled Learning
Junliang Luo, Farimah Poursafaei, Xue Liu
Detecting illicit nodes on blockchain networks is a valuable task for strengthening future regulation. Recent machine learning-based methods proposed to tackle the tasks are using…
Active Keyword Selection to Track Evolving Topics on Twitter
Sacha Lévy, Farimah Poursafaei, Kellin Pelrine +1
How can we study social interactions on evolving topics at a mass scale? Over the past decade, researchers from diverse fields such as economics, political science, and public heal…
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…