56 citations · 130 across the 16 of their papers we have counts for
6 papers · 1 filter
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets
Dominique Beaini, Shenyang Huang, Joao Alex Cunha +32
Recently, pre-trained foundation models have enabled significant advancements in multiple fields. In molecular machine learning, however, where datasets are often hand-curated, and…
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…
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…
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…
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…