Integrating Mamba and Transformer for Long-Short Range Time Series Forecasting

arXiv:2404.14757v1 Announce Type: new
Abstract: Time series forecasting is an important problem and plays a key role in a variety of applications including weather forecasting, stock market, and scientific simulations. Although transformers have proven to be effective in capturing dependency, its quadratic complexity of attention mechanism prevents its further adoption in long-range time series forecasting, thus limiting them attend to short-range range. Recent progress on state space models (SSMs) have shown impressive performance on modeling long range dependency due to …

arxiv cs.ai cs.lg forecasting mamba series time series time series forecasting transformer type