bwilder0 / clusternet
Code release for NeurIPS 2019 paper "End to End Learning and Optimization on Graphs"
☆86Updated 4 years ago
Related projects: ⓘ
- Source code for PairNorm (ICLR 2020)☆77Updated 4 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆190Updated 6 months ago
- Stochastic training of graph convolutional networks☆85Updated 2 years ago
- Measuring and Improving the Use of Graph Information in Graph Neural Networks☆82Updated last month
- Graph Representation Learning via Graphical Mutual Information Maximization☆109Updated 4 years ago
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆153Updated last year
- Graph Auto-Encoder in PyTorch☆81Updated last year
- AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning☆58Updated 5 years ago
- Official Implementation of ICML 2019 Paper. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing; an…☆122Updated 5 years ago
- An implementation of KDD paper "Graph Convolutional Networks with EigenPooling"☆46Updated 4 years ago
- [ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆107Updated 3 years ago
- Learning Steady-States of Iterative Algorithms over Graphs☆39Updated 6 years ago
- [IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"☆118Updated 4 months ago
- Supervised community detection with line graph neural networks☆88Updated 4 years ago
- PyTorch implementation of residual gated graph ConvNets, ICLR’18☆121Updated 5 years ago
- Code for NeurIPS'19 "Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks"☆76Updated last year
- Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"☆94Updated last year
- Conditional Structure Generation through Graph Variational Generative Adversarial Nets, NeurIPS 2019.☆53Updated 5 years ago
- Representation learning on large graphs using stochastic graph convolutions.☆138Updated 6 years ago
- code for the paper in NeurIPS 2019☆39Updated last year
- Implementations of "Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks"☆53Updated 4 years ago
- Official code for "vGraph: A Generative Model for Joint CommunityDetection and Node Representation Learning" (NeurIPS 2019)☆44Updated 10 months ago
- A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).☆154Updated 5 years ago
- AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations☆97Updated 4 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆264Updated last year
- ☆60Updated 3 years ago
- Multi-Graph Convolutional Neural Networks☆251Updated 6 years ago
- Code for reproducing results in GraphMix paper☆71Updated last year
- This is a TensorFlow implementation of the Adversarially Regularized Graph Autoencoder(ARGA) model as described in our paper: Pan, S., …☆186Updated 2 years ago
- Memory-Based Graph Networks☆101Updated 2 years ago