IEEE

Time Series Forecasting via Reinforcement-Learning-Based Model Combination

Abstract: Time series data permeates our daily existence and has been recognized as of significant importance for many sectors, such as energy, transportation, telecommunication, and health care.
GitHub

Is Mamba Effective for Time Series Forecasting?

We propose S-Mamba, a Mamba-based model for time series forecasting, which delegates the extraction of inter-variate correlations and temporal dependencies to a bidirectional Mamba block and a ...
GitHub

Time Series Foundation Model - TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

The official code for ["TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)"]. TEMPO is one of the very first open source Time Series Foundation Models for ...
IEEE

A Survey on Hyperparameters Optimization of Deep Learning for Time Series Classification

Abstract: Time series classification (TSC) is essential in various application domains to understand the system dynamics. The adoption of deep learning has advanced TSC, however its performance is ...