edouardpineau / A-simple-baseline-algorithm-for-graph-classificationLinks
Github page for the paper "A simple baseline algorithm for graph classification" presented at the R2L workshop of NIPS 2018
☆28Updated 4 years ago
Alternatives and similar repositories for A-simple-baseline-algorithm-for-graph-classification
Users that are interested in A-simple-baseline-algorithm-for-graph-classification are comparing it to the libraries listed below
Sorting:
- A Persistent Weisfeiler–Lehman Procedure for Graph Classification☆61Updated 4 years ago
- Code for the paper: "edGNN: A simple and powerful GNN for labeled graphs"☆43Updated 2 years ago
- Compute graph embeddings via Anonymous Walk Embeddings☆83Updated 6 years ago
- ☆31Updated 2 years ago
- Laplacian Change Point Detection for Dynamic Graphs (KDD 2020)☆28Updated last year
- 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 graph classification methods☆42Updated 4 years ago
- code for the paper in NeurIPS 2019☆40Updated 2 years ago
- Supervised community detection with line graph neural networks☆89Updated 4 years ago
- embedding attributed graphs☆57Updated 3 years ago
- Graph Recurrent Networks with Attributed Random Walks☆28Updated last year
- PyTorch Implementation of GraphTSNE, ICLR’19☆134Updated 6 years ago
- Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"☆52Updated 5 years ago
- This repository contains the TensorFlow implemtation of subgraph2vec (KDD MLG 2016) paper☆26Updated 7 years ago
- The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical…☆51Updated 2 years ago
- A Python implementation of a fast approximation of the Weisfeiler-Lehman Graph Kernels.☆24Updated 6 years ago
- Dynamic Youtube graphs☆27Updated 5 years ago
- Reimplementation of Graph Autoencoder by Kipf & Welling with DGL.☆65Updated 2 years ago
- Wasserstein Weisfeiler-Lehman Graph Kernels☆82Updated 9 months ago
- Data for "Understanding Isomorphism Bias in Graph Data Sets" paper.☆89Updated 5 years ago
- A Tensorflow 2.0 implementation of Graph Isomorphism Networks.☆55Updated 6 years ago
- Code for reproducing results in GraphMix paper☆72Updated 2 years ago
- Paper Code Learning Powerful Graph Neural Network Embeddings With Aid Of Transfer Learning☆40Updated 5 years ago
- A curated list of awesome graph representation learning.☆69Updated 4 years ago
- Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".☆43Updated 4 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 5 years ago
- Source code from the CIKM 2019 article "Gravity-Inspired Graph Autoencoders for Directed Link Prediction" by G. Salha, S. Limnios, R. Hen…☆45Updated last year
- Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper☆50Updated 4 years ago
- A package for computing Graph Kernels☆104Updated last year
- ☆19Updated 2 years ago