Ph.D. student Phillip Si and Assistant Professor Peng Chen developed Latent-EnSF, a technique that improves how ML models assimilate data to make predictions.

Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and economic uncertainty post-pandemic. Machine learning models can improve forecasting ...

Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

A new way to solve data scarcity: Turning qualitative reports into quantitative data with an LLM.

The proposed approach reduces computational cost while maintaining high predictive accuracy, making it suitable for large-scale applications JEONBUK-DO, South Korea, March 16, 2026 /PRNewswire/ -- ...

Forbes contributors publish independent expert analyses and insights. Jesse Damiani covers AI, ClimateTech, and emerging media. Mar 03, 2025, 04:06pm EST Mar 04, 2025, 03:48pm EST Image of Hurricane ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

Put down the pen and paper and shelve the spreadsheets. Artificial intelligence (AI) and advanced machine learning are the next-generation tools for demand forecasting in distribution. That was the ...

Magnetic resonance imaging (MRI) radiomics as predictor of clinical outcomes to neoadjuvant immunotherapy in patients with muscle invasive bladder cancer undergoing radical cystectomy. This is an ASCO ...