nd7141 / graph_datasetsLinks
Data for "Understanding Isomorphism Bias in Graph Data Sets" paper.
☆90Updated 5 years ago
Alternatives and similar repositories for graph_datasets
Users that are interested in graph_datasets are comparing it to the libraries listed below
Sorting:
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆68Updated 3 years ago
- ☆97Updated 2 years ago
- Reimplementation of Graph Autoencoder by Kipf & Welling with DGL.☆63Updated 2 years ago
- Graph meta learning via local subgraphs (NeurIPS 2020)☆126Updated last year
- Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxi…☆103Updated 4 years ago
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆97Updated 3 years ago
- Distance Encoding for GNN Design☆187Updated 4 years ago
- Implementation of Directional Graph Networks in PyTorch and DGL☆117Updated 4 years ago
- Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".☆190Updated 3 years ago
- Generating PGM Explanation for GNN predictions☆76Updated 2 years ago
- ☆62Updated 5 years ago
- SIGN: Scalable Inception Graph Network☆95Updated 5 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆273Updated 2 years ago
- Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R…☆134Updated 5 years ago
- Supervised community detection with line graph neural networks☆90Updated 5 years ago
- AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations☆102Updated 5 years ago
- A python package for graph kernels, graph edit distances, and graph pre-image problem.☆128Updated 5 months ago
- Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"☆211Updated 2 years ago
- Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric☆355Updated 5 months ago
- ☆155Updated 4 years ago
- Wasserstein Weisfeiler-Lehman Graph Kernels☆86Updated last year
- Code for the paper: "edGNN: A simple and powerful GNN for labeled graphs"☆43Updated 2 years ago
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆155Updated 3 years ago
- Subgraph Neural Networks (NeurIPS 2020)☆201Updated 4 years ago
- Geo2DR: A Python and PyTorch library for learning distributed representations of graphs.☆46Updated 2 years ago
- AAAI'21: Data Augmentation for Graph Neural Networks☆195Updated last year
- Paper Code Learning Powerful Graph Neural Network Embeddings With Aid Of Transfer Learning☆41Updated 5 years ago
- Official Pytorch Implementation of GraphiT☆109Updated 4 years ago
- PPRGo model in PyTorch, as proposed in "Scaling Graph Neural Networks with Approximate PageRank" (KDD 2020)☆126Updated 3 years ago
- Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch☆165Updated 3 years ago