Enhance Transformer Scalability

Background: The quadratic complexity of the self-attention mechanism in transformer architectures presents scalability limitations when processing very long sequences.

Question / Future Work: Exploring alternatives to the standard global self-attention mechanism, such as local or sparse attention methods, is necessary to enhance the scalability of the Physics-Spatiotemporal Masked Autoencoder (P-STMAE) for extremely long time series.