IEEE

Time Series Classification With Large Language Models via Linguistic Scaffolding

Abstract: Time series classification requires specialized models that can effectively capture temporal structures. Consequently, Large Language Models (LLMs) have emerged as promising candidates due ...
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 Novel Fusion and Feature Selection Framework for Multisource Time-Series Data Based on Information Entropy

Abstract: Information technology growth brings vast time-series data. Despite richness, challenges like redundancy emphasize the need for time-series data fusion research. Rough set theory, a valuable ...