Recent advances in machine learning have opened transformative avenues for investigating complex problems in string theory and geometry. By integrating sophisticated algorithms with theoretical ...

Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

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 ...

Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...