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 ...

A novel computer algorithm, or set of rules, that accurately predicts the orbits of planets in the solar system could be adapted to better predict and control the behavior of the plasma that fuels ...

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 ...

The authors devise an efficient quantum approach to address the van der Waals interactions due to photoexcitations by approximating the Bethe-Salpeter equation. Both attractive/repulsive forces can ...

Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...

For a topic that generates so much interest, it is surprisingly difficult to find a concise definition of machine learning that satisfies everyone. Complicating things further is the fact that much of ...

String theory and machine learning - two hot topics in physics, but how do you combine them? I'm talking to Thomas, a PhD ...

Machine learning is a powerful tool in the AI toolbox, but its limitations must be understood to use effectively. Machine learning has become the latest darling of the IT marketing space, a secret ...

We are excited to inform you that the current Machine Learning: Theory and Hands-On Practice with Python Specialization (taught by Professor Geena Kim) is being retired and will be replaced with a new ...