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Graph Convolution Network (Bayesian (A simple neural network module for…
Graph Convolution Network
Spatial-Temporal Domain
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition (AAAI 2018) :<3:
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (AAAI 2019)
Spatial Domain
Graph R-CNN for Scene Graph Generation (ECCV 2018 Facebook)
Diffusion-convolutional neural networks (NIPS 2016 Spotlight) :<3:
Diffusion Convolutional Recurrent Neural Networks: Data-Driven Traffic Forecasting
CNN4G : Learning Convolutional Neural Networks for Graphs(ICML 2016) :red_flag: :<3:
RGCNN: Regularized Graph CNN for Point Cloud Segmentation (ACM Multimedia 2018)
Spectral Domain
Chebyshev Polynomial(ChebNet)
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
(NIPS 2016)
Adaptive Kernel
Adaptive Graph Convolutional Neural Networks:<3: (AAAI 2018)
Dynamic Graph CNN for Learning on Point Clouds :red_flag:
GCN：Semi-Supervised Classification with Graph Convolutional Networks (ICLR 2017)
R-GCN : Modeling Relational Data with Graph Convolutional Networks (ESWC 2018) :<3:
Graph Wavelet Neural Network :<3:(ICLR 2019)
Graph U-Nets (ICML 2019)
Cayley Polynomial(CayleyNet)
CAYLEYNETS: SPECTRAL GRAPH CNNS WITH COMPLEX RATIONAL FILTERS (ICLR 2018)
Multivariate Polynomial(MotifNet)
MOTIFNET: A MOTIF-BASED GRAPH CONVOLUTIONAL NETWORK FOR DIRECTED GRAPHS(DSW 2018)
SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation(CVPR 2017)
Geometric Domain(Manifold)
MoNet ：Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs (CVPR 2017)
:<3:
GAT：Graph Attention Network (ICLR 2018) :<3:
DPGCNN：Dual-Primal Graph Convolutional Networks (CORR 2018 )
Relational Graph Attention Networks (ICLR 2019)
Hyperbolic Graph Neural Networks (NIPS 2019)
GCNN：Geodesic convolutional neural networks on Riemannian manifolds (ICCV 2015)
Multi-directional Geodesic Neural Networks via Equivariant Convolution
ACNN：(2016)
Bayesian
A simple neural network module for relational reasoning(DeepMind, NIPS 2017)
3D graph neural networks for rgbd semantic segmentation (CVPR 2017)
Relational inductive biases, deep learning, and graph networks.(大牛們 2018)
Geometric Deep Learning: Going beyond Euclidean data (SPM 2017)
Bayesian Semi-supervised Learning with Graph Gaussian Processes (NIPS 2018)
INFERENCE IN PROBABILISTIC GRAPHICAL MODELS
BY GRAPH NEURAL NETWORKS (ICLR 2018 workshop track)
Bayesian Graph Neural Network Using Non-Parametric Graph Learning (ICLR 2019)
Bayesian graph convolutional neural networks for semi-supervised classification (AA!I 2019)