Colloquium

Data-driven approaches match or outperform humans at a number of tasks, including pattern recognition in images and text or planning and strategy in rule-based games. The application of machine learning techniques is also promising for accelerating materials design. However, experimental data for training is typically scarce and sparse. The interplay between physics-based simulations and data-driven […]

Many complex nonequilibrium systems, including turbulent flows, are characterized by chaotic dynamics, a large number of degrees of freedom, and hierarchical, multiscale structure in space and time. In two vignettes, we describe some recent work aimed at developing and applying machine learning and data science tools for systems displaying these characteristics. The first vignette builds […]