Subsequently, a dual branch spatio-temporal graph neural network with an attention mechanism (DBSTGNN-Att) is designed for cellular network traffic prediction. Extensive experiments conducted on real-world datasets demonstrate that the proposed method outperforms baseline models, such as t...
Spatio-Temporal Graph neural network (STGNN). Trainer Trainer contains every information (such as dataset, optimizer, loss function, etc) for training each type of models mentioned above. Callbacks This module consists of callbacks which can be executed before/after some steps of training or testing...
KienMN / STGNN-for-Covid-in-Korea Star 28 Code Issues Pull requests Spatio-temporal graph neural network for predicting COVID-19 new cases in Korea. timeseries forecasting graph-neural-networks covid-19 spatio-temporal-graphs Updated Dec 8, 2021 Python Kumbong / GraphWavenet Star 0 Co...
DBSTGNN-Att: Dual Branch Spatio-Temporal Graph Neural Network with an Attention Mechanism for Cellular Network Traffic Prediction Subsequently, a dual branch spatio-temporal graph neural network with an attention mechanism (DBSTGNN-Att) is designed for cellular network traffic prediction... Z Cai,C ...
When both spatiotemporal features are present, spatiotemporal graph neural networks (STGNN) can handle data efficiently. Weiguo Zhu23proposed CorrSTN, a graphical model for traffic flow prediction based on spatiotemporal correlation information. The attention-based mechanism of STGNN can then model time...
Our empirical results demonstrate that the proposed STGNN significantly outperforms both the WMMSE benchmark and memoryless graph neural networks (GNNs) across all simulated scenarios, and converges to the globally optimal solution of the load-spillage algorithm, with lower computational complexity. ...
To overcome these challenges, we propose a novel graph deep learning-based decomposition method called the Spatio-Temporal Graph Neural Network for fleet-level PLR estimation (PV-stGNN-PLR). PV-stGNN-PLR decomposes the power timeseries data into aging and fluctuation c...
timeseries data obtained from the metering infrastructure in the grid as input, we develop a Spatial-Temporal Graph Neural Network based Denoising Autoencoder (STGNN-DAE) that performs MDI by accounting for both temporal and spatial ... S Kuppannagari,F Yao,C Cheung,... - 《Proceedings of th...
21-03-13 StemGNN🌟 NIPS 2020 Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting StemGNN 22-05-16 TPGNN NIPS 2022 Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks TPGNN 22-06-18 D2STGNN VLDB 2022 Decoupled Dynamic Spatial-Temporal Graph...
21-03-13 StemGNN🌟 NIPS 2020 Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting StemGNN 22-05-16 TPGNN NIPS 2022 Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks TPGNN 22-06-18 D2STGNN VLDB 2022 Decoupled Dynamic Spatial-Temporal Graph...