To address the aforementioned problems, we propose a novel model called Backbone-based Dynamic Spatio-Temporal Graph Neural Network (BDSTGNN). Intuitively, the continuous and smooth changes in graph structure m
Graph neural networks (GNNs) have always had a unique advantage in processing spatiotemporal data16,17,18,19. The graph structure in GNN20can efficiently gather spatiotemporal information and update the graph by employing the graph's adjacency matrix and the graph's convolution operation to fuse ...
STEP模型结合了一个预训练模型与一个时空图神经网络(STGNN)。预训练模型的目标是从长期历史时间序列中有效地学习时间模式,并生成分段级表示。这些表示为STGNN的短期时间序列输入提供了上下文信息,同时强化了处理时间序列之间建模的依赖性。 MTSMAE是一种针对多元时间序列预测的自监督预训练方法。基于掩码自动编码器(MAE)...
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...
23-03-25 STGNN🔥 TKDE 2023 Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey None 23-05-01 Diffusion Arxiv 2023 Diffusion Models for Time Series Applications: A Survey None 23-06-16 SSL TPAMI 2024 Self-Supervised Learning for Time Series Analysis: Tax...
Physics-guided spatio-temporal graph neural network (PG-STGNN)Long Short-Term Memory (LSTM)Accurate traffic flow forecasting at urban intersections is critical for optimizing transportation infrastructure and reducing congestion. This manuscript introduces a novel framework, the Physics-Guided Spatio-Temporal...
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 temporal graph ...
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 te...
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...
23-03-25 STGNN Arxiv 2023 Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey None 23-05-01 Diffusion Arxiv 2023 Diffusion Models for Time Series Applications: A Survey None 23-06-16 SSL TPAMI 2024 Self-Supervised Learning for Time Series Analysis: Taxono...