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 ...

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 ...

The absence of reliable data on fundamental economic indicators (e.g. real GDP), combined with structural shifts in the economy, can severely constrain the ability to conduct accurate macroeconomic ...

The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...

Researchers in China conceived a new PV forecasting approach that integrates causal convolution, recurrent structures, attention mechanisms, and the Kolmogorov–Arnold Network (KAN). Experimental ...

Accurately predicting solar irradiance and wind flow patterns is requisite for renewable energy forecasting—but precision alone simply isn't enough. The data must be actionable, fast, and seamlessly ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

The ITU Journal on Future and Evolving Technologies continues its in-depth coverage of machine learning for 5G and future networks.

As instigators of immunity, monoclonal antibodies are marvels of modern medicine, lab-made proteins that can treat cancers, ...