mala-lab/SEMPO
[NeurIPS 2025] Official implementation of "SEMPO: Lightweight Foundation Models for Time Series Forecasting"
This project helps operations engineers, financial analysts, or supply chain managers predict future trends from time-series data. It takes your historical time-series data, like sales figures or sensor readings, and produces highly accurate forecasts. This is ideal for anyone needing to make predictions with limited historical data or computational resources.
Use this if you need to accurately forecast future values from diverse time-series data, even when you have smaller datasets or want to conserve computational power.
Not ideal if you primarily work with static, non-sequential datasets for tasks like classification or regression, as this is specifically designed for time-series forecasting.
Stars
18
Forks
4
Language
Python
License
Apache-2.0
Category
Last pushed
Oct 23, 2025
Commits (30d)
0
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