Quater GCN

Quater-GCN (and related Graph Convolutional Networks or GCNs) represent a class of deep learning models designed to analyze data structured as graphs, capturing relationships between nodes (e.g., human joints, words in a sentence, brain regions). Current research focuses on improving GCN efficiency through architectural innovations like flattened layers and optimized GPU acceleration, as well as enhancing their application to diverse problems such as 3D human pose estimation, emotion recognition, and medical image analysis. These advancements are significant because they enable more accurate and efficient processing of complex relational data, impacting fields ranging from computer vision and natural language processing to healthcare and neuroscience.

Papers

November 4, 2024

ELU-GCN: Effectively Label-Utilizing Graph Convolutional Network
Jincheng Huang, Yujie Mo, Xiaoshuang Shi, Lei Feng, Xiaofeng Zhu
Convolutional Neural Network Graph Convolutional Network GCN Model GCN Based Quater GCN E Graph

April 30, 2024

Quater-GCN: Enhancing 3D Human Pose Estimation with Orientation and Semi-supervised Training
Xingyu Song, Zhan Li, Shi Chen, Kazuyuki Demachi
Deep Convolutional Neural Network Ground Truth Human Pose 3D Human 3D Human Pose Estimation Semi Supervised Training Head Orientation Quater GCN

March 16, 2024

ECRC: Emotion-Causality Recognition in Korean Conversation for GCN
J. K. Lee, T. M. Chung
Multi Task Learning Sentence Representation Causal Emotion Entailment Quater GCN Korean Nationwide Daily Conversation Corpus

August 22, 2023

Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks
Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding
Graph Convolution Network Quater GCN GPU Architecture

May 17, 2023

Dynamic Structural Brain Network Construction by Hierarchical Prototype Embedding GCN using T1-MRI
Yilin Leng, Wenju Cui, Chen Bai, Zheng Yanyan, Jian Zheng
Brain Connectivity T1 Weighted Quater GCN Cortical Hierarchy

March 31, 2023

HD-GCN:A Hybrid Diffusion Graph Convolutional Network
Zhi Yang, Kang Li, Haitao Gan, Zhongwei Huang, Ming Shi
Graph Convolutional Network Graph Convolution Information Diffusion GCN Model Quater GCN Diffusion Graph Convolutional Network

December 1, 2022

Architectural Implications of Embedding Dimension during GCN on CPU and GPU
Matthew Adiletta, David Brooks, Gu-Yeon Wei
Graph Neural Network Gene Level GNN Single GPU Box Dimension GNN Inference Quater GCN

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

July 12, 2022

From Spectral Graph Convolutions to Large Scale Graph Convolutional Networks
Matteo Bunino
Graph Convolutional Network Large Graph Semi Supervised Node Classification Spectral Graph Convolution Minibatch Stochastic Quater GCN

June 27, 2022

Unsupervised Domain Adaptation Using Feature Disentanglement And GCNs For Medical Image Classification
Dwarikanath Mahapatra
Domain Adaptation Unsupervised Domain Adaptation Medical Image Classification Medical Image Datasets Medical Image Analysis Task Feature Disentanglement Quater GCN

December 20, 2021

DMS-GCN: Dynamic Mutiscale Spatiotemporal Graph Convolutional Networks for Human Motion Prediction
Zigeng Yan, Di-Hua Zhai, Yuanqing Xia
Recurrent Neural Network Motion Prediction Temporal Graph Human Motion Prediction Temporal Convolutional Network Quater GCN