nd7141 / graph_datasets
Data for "Understanding Isomorphism Bias in Graph Data Sets" paper.
☆89Updated 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
- ☆92Updated last year
- Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxi…☆100Updated 3 years ago
- Distance Encoding for GNN Design☆187Updated 3 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆268Updated last year
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆69Updated 2 years ago
- Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".☆185Updated 2 years ago
- Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R…☆132Updated 4 years ago
- Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric☆345Updated 2 years ago
- PPRGo model in PyTorch, as proposed in "Scaling Graph Neural Networks with Approximate PageRank" (KDD 2020)☆127Updated 2 years ago
- AAAI'21: Data Augmentation for Graph Neural Networks☆189Updated 9 months ago
- PyTorch Geometric Signed Directed is a signed/directed graph neural network extension library for PyTorch Geometric. The paper is accepte…☆133Updated last week
- Implementation of Directional Graph Networks in PyTorch and DGL☆117Updated 3 years ago
- Supervised community detection with line graph neural networks☆89Updated 4 years ago
- ☆153Updated 3 years ago
- code for the paper in NeurIPS 2019☆40Updated last year
- Unsupervised Attributed Multiplex Network Embedding (AAAI 2020)☆148Updated last year
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆94Updated 2 years ago
- [NeurIPS 2021]: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architec…☆132Updated 2 years ago
- A Persistent Weisfeiler–Lehman Procedure for Graph Classification☆60Updated 3 years ago
- ☆62Updated 4 years ago
- ☆94Updated 2 years ago
- Hierarchical Inter-Message Passing for Learning on Molecular Graphs☆77Updated 3 years ago
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆155Updated 2 years ago
- AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations☆100Updated 4 years ago
- ☆55Updated 3 years ago
- SIGN: Scalable Inception Graph Network☆95Updated 4 years ago
- PyTorch Implementation of GraphTSNE, ICLR’19☆134Updated 5 years ago
- Compute graph embeddings via Anonymous Walk Embeddings☆82Updated 6 years ago
- NeurIPS 2019: HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs☆192Updated 4 years ago
- Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch☆164Updated 2 years ago