chrsmrrs / tudataset
☆94Updated last year
Alternatives and similar repositories for tudataset:
Users that are interested in tudataset are comparing it to the libraries listed below
- Data for "Understanding Isomorphism Bias in Graph Data Sets" paper.☆89Updated 5 years ago
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆94Updated 2 years ago
- ☆155Updated 3 years ago
- Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxi…☆100Updated 3 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆270Updated last year
- Implementation of Directional Graph Networks in PyTorch and DGL☆118Updated 3 years ago
- Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)☆87Updated last year
- Subgraph Neural Networks (NeurIPS 2020)☆193Updated 4 years ago
- Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".☆187Updated 2 years ago
- ☆80Updated 2 years ago
- Wasserstein Weisfeiler-Lehman Graph Kernels☆81Updated 6 months ago
- Explanation method for Graph Neural Networks (GNNs)☆64Updated 3 years ago
- An VGAE implementation using pytorch geometric.☆44Updated 4 years ago
- Distance Encoding for GNN Design☆187Updated 3 years ago
- here you can find the material used for our Tutorials☆100Updated 3 years ago
- ☆55Updated 2 years ago
- SIGN: Scalable Inception Graph Network☆95Updated 4 years ago
- GraphFramEx: a systematic evaluation framework for explainability methods on GNNs☆43Updated 11 months ago
- An open-source implementation of SEAL for link prediction in open graph benchmark (OGB) datasets.☆232Updated last year
- Geo2DR: A Python and PyTorch library for learning distributed representations of graphs.☆45Updated last year
- Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric☆346Updated 2 years ago
- Code for our paper "Attending to Graph Transformers"☆85Updated last year
- Hierarchical Inter-Message Passing for Learning on Molecular Graphs☆77Updated 3 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
- A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)☆126Updated last year
- ☆30Updated last year
- Implementation of Self-supervised Graph-level Representation Learning with Local and Global Structure (ICML 2021).☆79Updated 3 years ago
- This repository holds code and other relevant files for the Learning on Graphs 2022 tutorial "Graph Rewiring: From Theory to Applications…☆55Updated 2 years ago
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆157Updated last year
- Reimplementation of Graph Autoencoder by Kipf & Welling with DGL.☆66Updated 2 years ago