AlphaGalileo

Adapting to the Stream: An Instance-Attention GNN Method for Irregular Multivariate Time Series Data

DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...
IEEE

Triple Dynamic Graph Convolutional Recurrent Network for Traffic Prediction

Abstract: Effective traffic prediction is a critical component of traffic management, especially long-term traffic prediction, as it holds significance for urban traffic planning, traffic warning, ...
GitHub

Pull requests: Gabriele-Immordino/Spatio-temporal-Graph-Convolutional-Autoencoder-for-Transonic-Wing-Pressure-Distribution-Forecasting

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.
Frontiers

Deep learning-based object detection for environmental monitoring using big data

Introduction: Recent advances in artificial intelligence have transformed the way we analyze complex environmental data. However, high-dimensionality, spatiotemporal variability, and heterogeneous ...
Frontiers

Association prediction of lncRNAs and diseases using multiview graph convolution neural network

1 College of Computer Science and Engineering, Changsha University, Changsha, Hunan, China 2 Department of Information and Computing Science, College of Mathematics, Changsha University, Changsha, ...
Scientific Research Publishing

Li, F., Qiao, H. and Zhang, B. (2018) Discriminatively Boosted Image Clustering with Fully Convolutional Auto-encoders. Pattern Recognition, 83, 161-173.

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...
IEEE

Auto-encoder based Graph Convolutional Networks for Online Financial Anti-fraud

Abstract: Many practical problems can be formulated as graph-based semi-supervised classification problems. For example, online finance anti-fraud. Recently, many researchers attempt using deep ...