PyTorch TCN

A TCN, short for Temporal Convolutional Network, consists of dilated, causal 1D convolutional layers with the same input and output lengths .6 Tem 2021

3. Temporal Convolutional Network. Temporal Convolutional Networks, or simply TCN, is a variation of Convolutional Neural Networks for sequence modelling tasks, by combining aspects of RNN and CNN architectures .

CNNs don’t have the assumption that history is complete: Unlike RNNs, CNNs learn patterns within the time window. If you have missing data, CNNs should be useful . In a way, CNNs can look forward: RNN models only learn from data before the timestep it needs to predict.

A spatial–temporal Convolutional Neural Network is designed to automatically extract spatial–temporal features of the crowd . • The performance of anomaly detection is improved when the analysis is concentrated on the dynamic regions only.