Source Code

(Listed in alphabetical order of the model/algorithm/method names)


Graph Algorithms

BatchHL (Batch-Dynamic Distance Labelling): https://github.com/mufarhan/batchHL ( SIGMOD 2022 paper)

BatchHL+ (Improved Batch-Dynamic Distance Labelling): https://github.com/mufarhan/BatchHL-Plus ( VLDBJ 2023 paper)

FulHL (Fully Dynamic Distance Labelling): https://github.com/mufarhan/FulHL ( VLDBJ 2022 paper)

IncHL (Incremental Highway Cover Labelling): https://github.com/mufarhan/IncHL_Plus ( EBDT 2021 paper)

ParDHL (Parallel Dynamic Highway Cover Labelling): https://github.com/mufarhan/ParDHL ( WWW 2023 paper)

Rogas (Declarative Framework for Network Analytics): https://github.com/CornucopiaRG/Rogas ( VLDB 2016 paper)

Graph Machine Learning

GNN with Attention-Based Adaptive Aggregation (ASGAT): https://github.com/seanli3/asgat (ECML-PKDD 2021 paper)

Graph Restructuring via Adaptive Spectral Clustering (ASC): https://github.com/seanli3/graph_restructure (AAAI 2023 paper)

Spectral GNN with Feedback-Looped Filters (DFNet): https://github.com/wokas36/DFNets (NeurIPS 2019 paper)

GNN that Goes Beyond Weisfeiler-Lehman (GraphSNN): https://github.com/wokas36/GraphSNN (ICLR 2022 paper)

Graph Neighbourhood Neural Network (G3N): https://github.com/seanli3/G3N (ICLR 2023 paper)

Local Vertex Colouring GNN (LVC): https://github.com/seanli3/lvc (ICML 2023 paper)

Regularized Wasserstein Kernel (RWK): https://github.com/wokas36/RWK (ICDM 2021 paper)

Datasets


Courses