Researchers use statistical physics and "toy models" to explain how neural networks avoid overfitting and stabilize learning in high-dimensional spaces.

There’s a curious contradiction at the heart of today’s most capable AI models that purport to “reason”: They can solve routine math problems with accuracy, yet when faced with formulating deeper ...

Physicists and marine biologists built a quantitative framework that predicts how coral polyps collectively construct a variety of coral shapes. Since before she could remember, Eva Llabrés was a ...

A new study introduces choice engineering—a powerful new way to guide decisions using math instead of guesswork. By applying carefully designed mathematical models, researchers found they could ...

Understanding how wounds heal after injury could be a step closer thanks to a new mathematical model developed by researchers ...

Mathematics is deemed to be beyond figures. It is described as the foundation of resilience in society. Thus, this made Temitope Comfort Iroko, a PhD candidate in Mathematics at the University of ...

This study introduces MathEval, a comprehensive benchmarking framework designed to systematically evaluate the mathematical reasoning capabilities of large language models (LLMs). Addressing key ...