Graph Convolutional Network

Graph Convolutional Networks (GCNs) are a type of neural network designed to analyze data represented as graphs, focusing on learning relationships between interconnected nodes. Current research emphasizes improving GCN performance through techniques like graph pruning, transfer learning, and incorporating diverse data modalities (e.g., multi-omics, spatio-temporal data) into model architectures such as variational mode decomposition and dual graph convolutional networks. GCNs find broad application in diverse fields, including traffic prediction, drug response prediction, and disease diagnosis, offering powerful tools for analyzing complex relational data and extracting meaningful insights.

Papers

December 12, 2022

DeepCut: Unsupervised Segmentation using Graph Neural Networks Clustering
Amit Aflalo, Shai Bagon, Tamar Kashti, Yonina Eldar
Semantic Segmentation Image Segmentation Graph Convolutional Network Unsupervised Segmentation Cut and Approximate Deep Graph Clustering

December 9, 2022

November 28, 2022

Graph Convolutional Network for Multi-Target Multi-Camera Vehicle Tracking
Elena Luna, Juan Carlos San Miguel, José María Martínez, Marcos Escudero-Viñolo
Graph Convolutional Network Camera Trajectory Multi Camera Vehicle Tracking

November 25, 2022

Graph Convolutional Network-based Feature Selection for High-dimensional and Low-sample Size Data
Can Chen, Scott T. Weiss, Yang-Yu Liu
Feature Selection Graph Convolutional Network Graph Based High Dimension Graph Convolutional Small Sample

November 21, 2022

Learnable Graph Convolutional Attention Networks
Adrián Javaloy, Pablo Sanchez-Martin, Amit Levi, Isabel Valera
Graph Neural Network Graph Convolutional Network GNN Architecture Convolutional Attention

November 15, 2022

Neighborhood Convolutional Network: A New Paradigm of Graph Neural Networks for Node Classification
Jinsong Chen, Boyu Li, Kun He
Graph Neural Network Graph Representation Learning Node Classification Graph Convolutional Network Convolution Layer New Paradigm Neighborhood Component Analysis

October 12, 2022

JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks
Jian Kang, Qinghai Zhou, Hanghang Tong
Uncertainty Quantification Graph Convolutional Network High Uncertainty Value Semi Supervised Node Classification Trustworthy Graph

October 10, 2022

Pose-Guided Graph Convolutional Networks for Skeleton-Based Action Recognition
Han Chen, Yifan Jiang, Hanseok Ko
Action Recognition Graph Convolutional Network Skeleton Based Action Recognition Pose Network

September 25, 2022

Flattened Graph Convolutional Networks For Recommendation
Yue Xu, Hao Chen, Zengde Deng, Yuanchen Bei, Feiran Huang
Effective Recommendation Graph Convolutional Network Large Scale Recommendation Quater GCN Neighborhood Component Analysis

September 24, 2022

CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference
Ran Ran, Nuo Xu, Wei Wang, Gang Quan, Jieming Yin, Wujie Wen
Potential Scalability Graph Convolutional Network Homomorphic Encryption

September 16, 2022

Reinforcement Learning-Based Cooperative P2P Power Trading between DC Nanogrid Clusters with Wind and PV Energy Resources
Sangkeum Lee, Sarvar Hussain Nengroo, Hojun Jin, Taewook Heo, Yoonmee Doh, Chungho Lee, Dongsoo Har
Graph Convolutional Network Positive Reinforcement Wind Pressure Computing Cluster Peer to Peer Energy Trading

September 8, 2022

Analyzing the Effect of Sampling in GNNs on Individual Fairness
Rebecca Salganik, Fernando Diaz, Golnoosh Farnadi
Recommender System Mixed Effect Graph Convolutional Network Gene Level GNN Bias Mitigation Open Sampling Individual Fairness Downstream Forecasting Task

September 7, 2022

AST-GIN: Attribute-Augmented Spatial-Temporal Graph Informer Network for Electric Vehicle Charging Station Availability Forecasting
Ruikang Luo, Yaofeng Song, Liping Huang, Yicheng Zhang, Rong Su
Graph Convolutional Network Electric Vehicle

September 6, 2022

August 27, 2022

Spatial Relation Graph and Graph Convolutional Network for Object Goal Navigation
D. A. Sasi Kiran, Kritika Anand, Chaitanya Kharyal, Gulshan Kumar, Nandiraju Gireesh, Snehasis Banerjee, Ruddra dev Roychoudhury, Mohan Sridharan, Brojeshwar Bhowmick, Madhava Krishna
Graph Convolutional Network Robot Trajectory Object Goal Navigation Object Goal Navigation Task Spatial Graph

August 21, 2022

Representation Learning with Graph Neural Networks for Speech Emotion Recognition
Junghun Kim, Jihie Kim
Graph Neural Network Representation Learning Speech Emotion Recognition Graph Convolutional Network Expressive Neural

August 8, 2022

Occlusion-Aware Instance Segmentation via BiLayer Network Architectures
Lei Ke, Yu-Wing Tai, Chi-Keung Tang
Deep Convolutional Neural Network Instance Segmentation Graph Convolutional Network Video Instance Segmentation Two Layer Network Bilinear Convolutional Neural Network

August 5, 2022

3D Pose Based Feedback for Physical Exercises
Ziyi Zhao, Sena Kiciroglu, Hugues Vinzant, Yuan Cheng, Isinsu Katircioglu, Mathieu Salzmann, Pascal Fua
Training Data Graph Convolutional Network Learning Framework Physical Activity

Graph Convolutional Network

Papers

DeepCut: Unsupervised Segmentation using Graph Neural Networks Clustering

Multi-view Graph Convolutional Networks with Differentiable Node Selection

Scalable Graph Convolutional Network Training on Distributed-Memory Systems

Graph Convolutional Network for Multi-Target Multi-Camera Vehicle Tracking

Graph Convolutional Network-based Feature Selection for High-dimensional and Low-sample Size Data

Learnable Graph Convolutional Attention Networks

Neighborhood Convolutional Network: A New Paradigm of Graph Neural Networks for Node Classification

JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks

Pose-Guided Graph Convolutional Networks for Skeleton-Based Action Recognition

Flattened Graph Convolutional Networks For Recommendation

CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference

Reinforcement Learning-Based Cooperative P2P Power Trading between DC Nanogrid Clusters with Wind and PV Energy Resources

Analyzing the Effect of Sampling in GNNs on Individual Fairness

AST-GIN: Attribute-Augmented Spatial-Temporal Graph Informer Network for Electric Vehicle Charging Station Availability Forecasting

CP-AGCN: Pytorch-based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy

Graph-PHPA: Graph-based Proactive Horizontal Pod Autoscaling for Microservices using LSTM-GNN

Spatial Relation Graph and Graph Convolutional Network for Object Goal Navigation

Representation Learning with Graph Neural Networks for Speech Emotion Recognition

Occlusion-Aware Instance Segmentation via BiLayer Network Architectures

3D Pose Based Feedback for Physical Exercises