IEEE

iBACon: imBalance-Aware Contrastive Learning for Time Series Forecasting

Abstract: Time series forecasting (TSF) has gained significant attention as a widely explored research area in diverse applications. Existing methods, which focus on improvements in the most common ...
Frontiers

A comparative study of time series foundation models for hand, foot, and mouth disease forecasting: TimesFM, Moirai, and traditional approaches

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 ...
Time

AI Is Learning to Predict the Future—And Beating Humans at It

Reactions to Kimmel's suspension, Trump publicly rebukes Putin, and more Length: Long Speed: 1.0x Every three months, participants in the Metaculus forecasting cup try to predict the future for a ...
The New York Times

The Future of Weather Prediction Is Here. Maybe.

Thanks to A.I., companies like WindBorne hope to usher in a golden age of forecasting. But they rely in part on government data — and the agency that provides it is in turmoil. A WindBorne weather ...
Frontiers

Deep learning approaches for time series prediction in climate resilience applications

1 Sichuan Digital Economy Industry Development Research Institute, Xi‘an Jiaotong University, Chengdu, China 2 Department of Art and Design, Taiyuan University, Taiyuan, Shanxi, China Introduction: ...
GitHub

FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting

🚩 Updates (2025-04-24) Our paper has been featured on 时序人, QuantML, and PaperWeekly. 🚩 Updates (2025-02-27) Initial version available on arXiv FinTSB. FinTSB is a comprehensive and practical ...
IEEE

Causal-TSF: A Causal Intervention Approach to Mitigate Confounding Bias in Time Series Forecasting

Abstract: Time series forecasting, aiming to learn models from historical data and predict future values in time series, is a fundamental research topic in machine learning. However, few efforts have ...
Scientific Research Publishing

Comparative Analysis of ARIMA and NNAR Models for Time Series Forecasting ()

This paper presents a comparative study of ARIMA and Neural Network AutoRegressive (NNAR) models for time series forecasting. The study focuses on simulated data generated using ARIMA(1, 1, 0) and ...