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 ...

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

Welcome to the website of the CS theory group at CU Boulder! Our faculty and students research all aspects of theoretical computer science, from core areas such as algorithms, complexity, and ...

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 ...

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

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 ...

For mathematicians and computer scientists, this was often a year of double takes and closer looks. Some reexamined foundational principles, while others found shockingly simple proofs, new techniques ...

“Artificial Intelligence” as we know it today is, at best, a misnomer. AI is in no way intelligent, but it is artificial. It remains one of the hottest topics in industry and is enjoying a renewed ...

On November 16, IDEAL hosted a workshop focused on new directions on robustness in machine learning as part of the fall 2021 special quarter. Machine learning systems are widely deployed to facilitate ...