HongtengXu / gwlLinks
Gromov-Wasserstein Learning for Graph Matching and Node Embedding
☆72Updated 5 years ago
Alternatives and similar repositories for gwl
Users that are interested in gwl are comparing it to the libraries listed below
Sorting:
- Gromov-Wasserstein Factorization Models for Graph Clustering (AAAI-20)☆31Updated 2 years ago
- Code for Optimal Transport for structured data with application on graphs☆101Updated 2 years ago
- Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching☆44Updated 5 years ago
- Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport☆37Updated 4 years ago
- Code for reproducing results in GraphMix paper☆72Updated 2 years ago
- Code for Graphite iterative graph generation☆59Updated 6 years ago
- [ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆110Updated 4 years ago
- Pytorch Implementation of Graph Convolutional Kernel Networks☆54Updated 2 years ago
- Source code for PairNorm (ICLR 2020)☆78Updated 5 years ago
- Wasserstein Weisfeiler-Lehman Graph Kernels☆82Updated 10 months ago
- Contains the code relative to the paper Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning https://arxiv.org/abs…☆21Updated 5 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆197Updated last year
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆104Updated 5 years ago
- Learning Autoencoders with Relational Regularization☆46Updated 4 years ago
- Official Implementation of ICML 2019 Paper. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing; an…☆124Updated 6 years ago
- Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"☆52Updated 5 years ago
- ☆25Updated 5 years ago
- Conditional Structure Generation through Graph Variational Generative Adversarial Nets, NeurIPS 2019.☆53Updated 5 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 5 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- Graph Representation Learning via Graphical Mutual Information Maximization☆116Updated 5 years ago
- AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations☆100Updated 5 years ago
- Code accompanying the NeurIPS 2019 paper "GOT: An Optimal Transport framework for Graph comparison"☆41Updated last year
- ☆37Updated 6 years ago
- The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)☆46Updated 4 years ago
- informal exposition of Weisfeiler-Leman similarity☆28Updated 4 years ago
- Memory-Based Graph Networks☆103Updated 3 years ago
- Graph meta learning via local subgraphs (NeurIPS 2020)☆125Updated 11 months ago
- ☆62Updated 4 years ago
- Implicit Graph Neural Networks☆62Updated 3 years ago