deezer / linear_graph_autoencodersLinks
Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R. Hennequin, M. Vazirgiannis) + k-core framework implementation from IJCAI 2019 article "A Degeneracy Framework for Scalable Graph Autoencoders" (G. Salha, R. Hennequin, V.A. Tran, M. Vazirgiannis)
☆132Updated 4 years ago
Alternatives and similar repositories for linear_graph_autoencoders
Users that are interested in linear_graph_autoencoders are comparing it to the libraries listed below
Sorting:
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆195Updated last year
- Distance Encoding for GNN Design☆186Updated 4 years ago
- Supervised community detection with line graph neural networks☆89Updated 4 years ago
- Official Implementation of ICML 2019 Paper. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing; an…☆124Updated 5 years ago
- Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddin…☆227Updated last year
- Graph Auto-Encoder in PyTorch☆81Updated 2 years ago
- PyTorch Implementation of GraphTSNE, ICLR’19☆134Updated 6 years ago
- This is a TensorFlow implementation of the Adversarially Regularized Graph Autoencoder(ARGA) model as described in our paper: Pan, S., …☆184Updated 3 years ago
- Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"☆210Updated last year
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆272Updated 2 years ago
- AAAI'21: Data Augmentation for Graph Neural Networks☆193Updated last year
- This is the implementation of paper 'Variational Graph Auto-Encoder' in NIPS Workshop on Bayesian Deep Learning, 2016.☆74Updated 7 years ago
- AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations☆100Updated 4 years ago
- Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" …☆319Updated last year
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆155Updated 2 years ago
- Official code for "vGraph: A Generative Model for Joint CommunityDetection and Node Representation Learning" (NeurIPS 2019)☆45Updated last year
- PPRGo model in PyTorch, as proposed in "Scaling Graph Neural Networks with Approximate PageRank" (KDD 2020)☆126Updated 3 years ago
- Graph Representation Learning via Graphical Mutual Information Maximization☆116Updated 5 years ago
- ☆51Updated 3 years ago
- Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".☆187Updated 3 years ago
- Code for reproducing results in GraphMix paper☆72Updated 2 years ago
- [ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision☆157Updated 2 years ago
- [IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"☆121Updated last year
- Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"☆97Updated last year
- A tensorflow implementation of GCN-LPA☆99Updated 5 years ago
- Code for NeurIPS'19 "Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks"☆76Updated 2 years ago
- Code for "M. Zhang, Z. Cui, M. Neumann, and Y. Chen, An End-to-End Deep Learning Architecture for Graph Classification, AAAI-18".☆178Updated 7 years ago
- Representation learning on large graphs using stochastic graph convolutions.☆138Updated 7 years ago
- PyTorch code for "Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions"☆102Updated 4 years ago
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆94Updated 3 years ago