Abstract: Multivariate time series forecasting (MTSF) endeavors to predict future observations given historical data, playing a crucial role in time series data management systems. With advancements ...

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 ...

This study investigates whether anomaly-aware modeling can improve stock price forecasting by incorporating signals that highlight unusual market behavior. Financial time series often contain sudden ...

Ant International currently deploys the Falcon TST AI Model to forecast cashflow and FX exposure with more than 90% accuracy Ant International, a leading global digital payment, digitisation, and ...

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 ...

Kairos is a flexible time series foundation model designed to handle the dynamic and heterogeneous nature of real-world time series data. Unlike existing models that rely on rigid, non-adaptive ...

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 Chongqing Key Laboratory of Childhood Nutrition and Health, Department of Nephrology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and ...

This broad data foundation enables Moirai 2.0 to generalize across countless forecasting tasks and domains. With dramatically reduced model size and improved speed, high-quality forecasting can now be ...

Temperature impacts every part of the world. Meteorological analysis and weather forecasting play a crucial role in sustainable development by helping reduce the damage caused by extreme weather ...