Recent studies have shown great performance of Transformer-based models in long-term time series forecasting due to their ability in capturing long-term dependencies. However, Transformers have their ...

The goal of this paper is to test three classes of neural network (NN) architectures based on four-dimensional (4D) hypercomplex algebras for multivariate time series forecasting. We evaluate ...

This study bridges classical time-series econometrics with modern machine learning by establishing theoretical performance guarantees for recurrent neural networks (RNNs) applied to complex ...