Temporal graph benchmark for machine learning on temporal graphs
Abstract We present the Temporal Graph Benchmark (TGB), a collection of challenging and
diverse benchmark datasets for realistic, reproducible, and robust evaluation of machine …
diverse benchmark datasets for realistic, reproducible, and robust evaluation of machine …
Evaluating graph neural networks for link prediction: Current pitfalls and new benchmarking
Link prediction attempts to predict whether an unseen edge exists based on only a portion of
the graph. A flurry of methods has been created in recent years that attempt to make use of …
the graph. A flurry of methods has been created in recent years that attempt to make use of …
Towards foundation models for knowledge graph reasoning
Revisiting link prediction: A data perspective
Link prediction, a fundamental task on graphs, has proven indispensable in various
applications, eg, friend recommendation, protein analysis, and drug interaction prediction …
applications, eg, friend recommendation, protein analysis, and drug interaction prediction …
Diffusion-based negative sampling on graphs for link prediction
Link prediction is a fundamental task for graph analysis with important applications on the
Web, such as social network analysis and recommendation systems,\etc\Modern graph link …
Web, such as social network analysis and recommendation systems,\etc\Modern graph link …
Foundation models for the electric power grid
Foundation models (FMs) currently dominate news headlines. They employ advanced deep
learning architectures to extract structural information autonomously from vast datasets …
learning architectures to extract structural information autonomously from vast datasets …