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 ...
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 ...
CMU School of Computer Science

Databases in 2025: A Year in Review

The world tried to kill Andy off but he had to stay alive to to talk about what happened with databases in 2025.
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 ...