Long Range Graph Benchmark, NeurIPS 2022 Track on D&B
Awesome graph-level learning methods. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in graph representation learning, graph regression and graph classification to join this project as contribut…
🗂 Graph Learning Indexer: a contributor-friendly and metadata-rich platform for graph learning benchmarks. Dataloading, Benchmarking, Tagging, and more!
I/O utilities and datasets for algebraic-graphs
This repository contains parameter generation, simulation, and encapsulation code for the DiTEC-WDN dataset. Feel free to use it on your "private" WDN!
A package for downloading and working with graph datasets
A sampling based method for scaling graph (network) data sets.
This Myket Dataset comprises Android application install interactions from a subset of users in the Myket Android application market.
ParaGrapher: Graph Loading API and Library
MS-BioGraphs-Validation: Validation Code for MS-BioGraphs
ParaGrapher: Graph Loading API and Library
PyTorch code for an effective way of making a Molecular Graph Dataset in Torch Geometric involving a pair of graphs from chemical SMILE strings
Power flow, N-1 contingency screening, DC optimal power flow with LMPs and cascading failure simulation for transmission grids. NumPy and SciPy, reads MATPOWER cases, ships the IEEE and PGLib-OPF systems, validated against PYPOWER.
This is a repository of the code used for the experimental work in my Bachelor thesis on Approximation Algorithms for Graph Edit Distance (GED). It includes implementations, benchmarking scripts, and evaluation methods for comparing GED approximation algorithms with exact computations.
Code for the paper: How Powerful Are Classic Graph Neural Networks? A Survey
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