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 ...

In this online data science specialization, you will apply machine learning algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Beginning ...

Experiments and machine learning reveal that grain boundary sliding governs the exceptional room-temperature ductility of an ...

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 ...

A machine learning-guided search has produced a tungsten bronze oxide ceramic that combines a high dielectric constant, ...

Two recent collaborations between mathematicians and DeepMind demonstrate the potential of machine learning to help researchers generate new mathematical conjectures. Mathematicians often work ...

In the machine learning world, the sizes of artificial neural networks — and their outsize successes — are creating conceptual conundrums. When a network named AlexNet won an annual image recognition ...

Sofia University, a WASC Senior College and University Commission (WSCUC)-accredited institution, is expanding its graduate ...

Machine learning and neural networks are two common terms in AI -- but what do they mean, and how do they differ? What exactly is machine learning? Machine learning is a subset of AI. ML uses an ...