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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 ...

1 Faculty of Electrical Technology and Engineering, Universiti Teknikal Malaysia Melaka (UTeM), Melaka, Malaysia. 2 Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia ...

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

Abstract: Forecasting future values in multivariate time series is a critical challenge in many application domains, such as agriculture, transportation, energy, etc. Recently, Large Language Models ...

Time series econometrics and forecasting constitute a dynamic research area that combines sophisticated statistical methodologies with economic theory to model, interpret and predict economic and ...

This repository contains the source code associated with the publication Winner-Takes-All for Multivariate Probabilistic Time Series Forecasting (ICML 2025). We introduce TimeMCL, a method leveraging ...