The future of machine learning and theory. Machine learning used in both experiment and theory has led to a blurring of the lines between the two traditionally disparate camps. In fact, some posit ...

Researchers are using machine learning, symbolic regression, and high-performance computing to explore and classify string ...

Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends ...

Some of the most encouraging results for reaction-enhancing catalysts come from one material in particular: tin (Sn). While ...

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

Catalog description: Presents the underlying theory behind machine learning in proofs-based format. Answers fundamental questions about what learning means and what can be learned via formal models of ...

Maarten Sap, a computer scientist at Carnegie Mellon University, fed more than 1,000 theory of mind tests into large language models and found that the most advanced transformers, like ChatGPT and ...

AI/ML systems intersect with machine learning theory and software engineering. The system should scale to large data sets, train models reliably and cost-effectively, and serve the model ...

The Master of Science in Machine Learning Engineering plan of study requires a total of 45 credits; 12 credits in core courses; 6 credits of mathematical theory, 3 credits in each applications and ...