The code for paper:Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values. Getting Start Install requirements.pip install -r requirements.txt Download data. Download Metr-LA, E
2018年 Google、Facebook 相继发表了研究成果,其中一篇叙述比较全面的论文是 "An Empirical Evaluation of Generic Convolutional and Recurrent Networks"。业界将这一新架构命名为时间卷积网络(Temporal Convolutional Network,TCN)。TCN 模型以 CNN 模型为基础,并做了如下改进: 适用序列模型:因果卷积(Causal Convolution)...
Therefore, we use LSTM and temporal convolution network (TCN) architecture to minimize the loss 'ðy0; . . .; yT ; F ðx0; . . .; xT ÞÞ for effective modeling and prediction of time-series weather data. 5.1 DNN with long short-term memory (LSTM) layers DNN with long ...
To this end, we propose a novel robust temporal feature network (RTFN) for feature extraction in time series classification, containing a temporal feature network (TFN) and a long short-term memory (LSTM)-based attention network (LSTMaN). TFN is a residual structure with multiple convolutional...
Secondly, the dilated causal convolution layer of the MTCN has the function of information memory and can learn time series characteristics. The stack of residual blocks is employed to form the network structure of the MTCN. The output layer selects the convolution layer instead of the fully ...
3 Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation 4 ByGCN: Spatial Temporal Byroad-Aware Graph Convolution Network for Traffic Flow Prediction in Road Networks 5 Spatio-temporal Graph Normalizing Flow for Probabilistic Traffic Prediction 6 Irregularity-Informed...
37 introduce an asynchronous GCN for predicting irregular traffic series. It captures spatial dependencies via asynchronous diffusion and performs time-aware convolution on inconsistent time flows using a transformable network. Zhang et al.38 propose an adaptive interactive multi-level network for traffic ...
Spectral Graph Convolution: 此文使用了最早期的谱图卷积提取数据的空间依赖。首相将normalized graph Laplacian的特征向量作为GFT的基底将数据和可学习参数转到频域,然后将在频域将参数与数据在频域做点积(等效于在空域在卷积),最后将数据用IGFT转回空域:
The TCN uses causal convolutions, which only operate on data before the current element, to process data in the temporal order. To handle long sequences, dilated convolution is used such that the receptive field grows exponentially with the depth of the network. This feature is especially ...
3 Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation 链接:https://arxiv.org/abs/2403.11960 作者:Baoyu Jing,Dawei Zhou,Kan Ren,Carl Yang 关键词:插补,时空图神经网络,因果注意力 CASPER 4 ByGCN: Spatial Temporal Byroad-Aware Graph Convolution Network for Tra...