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Found 4 papers, 1 papers with code
Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting--Full Version
(i) Linear complexity: we introduce a novel patch attention with linear complexity.
Towards Spatio-Temporal Aware Traffic Time Series Forecasting--Full Version
Such spatio-temporal agnostic models employ a shared parameter space irrespective of the time series locations and the time periods and they assume that the temporal patterns are similar across locations and do not evolve across time, which may not always hold, thus leading to sub-optimal results.
Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting -- Full version
For example, speed sensors are deployed in different locations in a road network, where the speed of a specific location across time is captured by the corresponding sensor as a time series, resulting in multiple speed time series from different locations, which are often correlated.
Correlated Time Series Forecasting using Deep Neural Networks: A Summary of Results
To enable accurate forecasting on such correlated time series, this paper proposes two models that combine convolutional neural networks (CNNs) and recurrent neural networks (RNNs).
