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 ...

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 ...

The country's Consumer Price Index rose at an annual rate of 2.7% in December, the Bureau of Labor Statistics announced Tuesday. The number, the final one of 2025, was in line with economists' ...

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: To address the limitations of traditional time series models in capturing nonlinear inflation dynamics and deep learning's susceptibility to overfitting with limited data, this study ...

This project provides a modern, well-structured implementation of hierarchical time series forecasting methods. It supports various forecasting algorithms (ARIMA, Prophet, LSTM) and reconciliation ...

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 ...