Models That Minimize the Rate of Information Loss

Explore the cutting-edge approach to modeling complex systems in this 40-minute lecture by Bruce Turkington at the Alan Turing Institute. Delve into the challenges of reducing intricate models across scientific disciplines to a manageable number of variables for practical computation and accurate prediction. Discover how powerful statistical methods, leveraging large volumes of data, are revolutionizing the modeling paradigm. Learn about the emerging combination of statistical inference, high-throughput computation, and physical laws in model development. Examine applications in collective dynamics, molecular modeling, cell biology, and fluid dynamics. Follow the lecture's progression from introduction to conceptual framework, parametric modeling, residual analysis, optimization techniques, and statistical mechanics. Gain insights into Burgers equations, Statistical Fluid Dynamics, and simulation methods before concluding with a comprehensive summary of this innovative approach to data-driven modeling of complex systems.