There are 1 repository under gcnn topic.
Code for "Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction" CVPR 2020
Code for A GRAPH-CNN FOR 3D POINT CLOUD CLASSIFICATION (ICASSP 2018)
Embedded Graph Convolutional Neural Networks (EGCNN) in TensorFlow
Dynamic Graph Convolutional Neural Network for 3D point cloud semantic segmentation
Code for: "Skeleton-Graph: Long-Term 3D Motion Prediction From 2D Observations Using Deep Spatio-Temporal Graph CNNs", ICCV2021 Workshops
Automated Headline generation and Aspect Based Sentiment Analysis
Algorithms for prediction of congestion from Network State
Code for HAR-GCNN: Deep Graph CNNs for Human Activity Recognition From Highly Unlabeled Mobile Sensor Data, IEEE PerCom CoMoRea 2022
Marker-Based Motion Capture Data Denoising
Graph Analysis Course Notes
A TensorFlow 2 implementation of Graph Convolutional Networks (GCN)
Graph convolutional networks for structural learning of proteins
Weather prediction on stereo images using a graph equivariant convolutional neural network.
A Graph Convolutional Network, or GCN, is an approach for semi-supervised learning on graph-structured data. It is based on an efficient variant of convolutional neural networks which operate directly on graphs.
ECE271B: Statistical Learning II Final Project with David Glukhov
A collections of all deep learning experiments we have throughout the deep learning courses
Yale Collab with Aarthi (Smita Krishnaswamy group) where I built signalling knowledge graphs to capture cell communications.