TimeDistill: Efficient Long-Term Time Series Forecasting with MLP via Cross-Architecture Distillation Code KDD 2026 LoFT-LLM: Low-Frequency Time-series Forecasting with Large Language Models Code KDD ...

Mr. Furman, a contributing Opinion writer, was the chairman of the White House Council of Economic Advisers from 2013 to 2017. See more of our coverage in your search results.Encuentra más de nuestra ...

A unified foundation model for medical time series — pretrained on open access and ethics board-approved medical corpora — offers the potential to reduce annotation burdens, minimize model ...

This project computes a Personalized Consumer Price Index (CPI) for each user based on their unique spending behavior. Instead of relying on the national “CPI-U,” this system builds a user-specific ...

1 Department of Computer Science, University of Mary Washington, Fredericksburg, USA. 2 Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, USA. This paper explores ...

Abstract: Due to the intrinsic complexity of time series forecasting within power systems, artificial intelligence has emerged as a promising pathway for predictive analytics. Although time series ...

In this tutorial, we build an advanced agentic AI system that autonomously handles time series forecasting using the Darts library combined with a lightweight HuggingFace model for reasoning. We ...