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.

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 system for forecasting weather and predicting future climate uses artificial intelligence to achieve results comparable with the best existing models while using much less computer power, ...

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 ...

AI market forecasting uses predictive analytics and strategic planning tools to anticipate demand shifts, optimize decisions, ...

A groundbreaking AI model, GenCast, is revolutionizing weather forecasting by generating rapid, probabilistic global ...

Machine learning models can be incredibly valuable tools for business leaders. They can aid in interpreting historic data, making decisions for future initiatives, helping to improve the customer ...

Machine learning, AI, automation and and prediction are rapidly evolving the digital landscape. Can digital twins be the ...

If you are interested in learning more about artificial intelligence and specifically how different areas of AI relate to each other then this quick guide providing an overview of Machine Learning vs ...

Adam M. Root argues businesses must anchor ML in customer problems, not technology. He details a strategy using ...