vermaMachineLearning / FGSDLinks
Graph Feature Representation/Vector Based On The Family Of Graph Spectral Distances (NIPS 2017).
☆24Updated 5 years ago
Alternatives and similar repositories for FGSD
Users that are interested in FGSD are comparing it to the libraries listed below
Sorting:
- Compute graph embeddings via Anonymous Walk Embeddings☆83Updated 7 years ago
- A Persistent Weisfeiler–Lehman Procedure for Graph Classification☆63Updated 4 years ago
- A convolutional neural network for graph classification in PyTorch☆91Updated 6 years ago
- Code for Graphite iterative graph generation☆59Updated 6 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆105Updated 5 years ago
- LDP for graph classification☆23Updated 5 years ago
- Equivalence Between Structural Representations and Positional Node Embeddings☆22Updated 5 years ago
- Code for the paper: "edGNN: A simple and powerful GNN for labeled graphs"☆43Updated 2 years ago
- PyTorch Implementation of GraphTSNE, ICLR’19☆137Updated 6 years ago
- Gaussian node embeddings. Implementation of "Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking".☆175Updated 2 years ago
- Implementation of the Multiscale Laplacian Graph Kernel☆19Updated 5 years ago
- TensorFlow implementation of Deep Graph Infomax☆62Updated 6 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆36Updated 5 years ago
- ☆35Updated 6 years ago
- A comprehensive collection of GNN works in NeurIPS 2019.☆21Updated 5 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
- Learning neural network embeddings in hyperbolic spaces☆14Updated 5 years ago
- Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"☆53Updated 5 years ago
- Deprecated repository for "Deep Learning with Topological Signatures"☆36Updated 5 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 5 years ago
- ☆12Updated 4 years ago
- Graph Auto-Encoder in PyTorch☆81Updated 2 years ago
- Deep Graph Mapper: Seeing Graphs through the Neural Lens☆58Updated 2 years ago
- Graph kernels☆56Updated 3 years ago
- ☆16Updated 5 years ago
- Code for "M. Zhang, Y. Chen, Weisfeiler-Lehman Neural Machine for Link Prediction, KDD 2017 oral"☆56Updated 7 years ago
- OhmNet: Representation learning in multi-layer graphs☆83Updated 5 years ago
- SIGN: Scalable Inception Graph Network☆95Updated 4 years ago
- Wasserstein Weisfeiler-Lehman Graph Kernels☆83Updated last year
- Reference implementation of the paper VERSE: Versatile Graph Embeddings from Similarity Measures☆132Updated 4 years ago