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.

Picture a single forecasting mistake triggering a cascade of negative consequences, such as surplus inventory, strained supplier relationships and disappointed customers. In today's world, accurate ...

Read more about Artificial intelligence boosts financial forecasting accuracy in banking sector on Devdiscourse ...

A range of national meteorological services across Europe and ECMWF have launched Anemoi, a framework for creating machine learning (ML) weather forecasting systems. Named after the Greek gods of the ...

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 ...

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 ...

Scientists develop a forecasting system that predicts high-risk windows and regions for solar superflares, using 50 years of X-ray data and machine learning techniques.

Joshua S. Fu received funding from U. S. EPA for wildfire and human health studies. Wildfire smoke from Canada’s extreme fire season has left a lot of people thinking about air quality and wondering ...

A team of scientists from around the world has created the first system that can predict when and where extremely powerful ...