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 ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting expertise.From neural networks to N ...

There are three key factors for the success of machine learning applications; that is, algorithm, data, and computational resource. Prof. Zhi-Hua Zhou of Nanjing University disclosed that, classical ...

A key objective of behavioral science research is to better understand how people make decisions in situations where outcomes are unknown or uncertain, which entail a certain degree of risk. Subscribe ...

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 ...