gear / gfnnLinks
Graph Filter Neural Network (ICPR'20)
☆48Updated 5 years ago
Alternatives and similar repositories for gfnn
Users that are interested in gfnn are comparing it to the libraries listed below
Sorting:
- Graph Representation Learning via Graphical Mutual Information Maximization☆117Updated 5 years ago
- ☆62Updated 5 years ago
- Source code for PairNorm (ICLR 2020)☆79Updated 5 years ago
- Official Implementation of ICML 2019 Paper. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing; an…☆125Updated 6 years ago
- Implementation of Graph Convolutional Networks in TensorFlow☆45Updated 7 years ago
- ☆30Updated 5 years ago
- Measuring and Improving the Use of Graph Information in Graph Neural Networks☆83Updated last year
- Code for NeurIPS'19 "Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks"☆76Updated 2 years ago
- Graph Convolutional Neural Networks with Complex Rational Spectral Filters☆26Updated 6 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆106Updated 4 months ago
- The code for our ICLR paper: StructPool: Structured Graph Pooling via Conditional Random Fields☆58Updated 5 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 4 years ago
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆137Updated 2 years ago
- Code for reproducing results in GraphMix paper☆72Updated 2 years ago
- Variational Graph Convolutional Networks☆23Updated 5 years ago
- Representation Learning on Graphs with Jumping Knowledge Networks☆39Updated 6 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆199Updated last year
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆36Updated 3 years ago
- A dgl implementation of Jumping Knowledge Networks (arXiv 1806.03536)☆38Updated 6 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆273Updated 2 years ago
- Codes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"☆89Updated 4 years ago
- [ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆111Updated 4 years ago
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆97Updated 3 years ago
- Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddin…☆232Updated 2 years ago
- [IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"☆123Updated last year
- ☆138Updated 2 years ago
- Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"☆97Updated 2 years ago
- AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations☆101Updated 5 years ago
- [ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision☆159Updated 2 years ago
- Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".☆190Updated 3 years ago