Regularization by Noise for the Stochastic Transport Equation
Hausdorff Center for Mathematics via YouTube
Python, Prompt Engineering, Data Science — Build the Skills Employers Want Now
MIT Sloan AI Adoption: Build a Playbook That Drives Real Business ROI
Overview
Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off
One annual plan covers every course and certificate on Coursera. 40% off for a limited time.
Get Full Access
Explore a 57-minute lecture on regularization by noise for the stochastic transport equation, presented by Lisa Beck at the Hausdorff Center for Mathematics. Delve into the intricacies of weak (L∞-) solutions for both deterministic and stochastic transport equations, examining the interplay between drift, unknown variables, and Brownian motion. Discover how the introduction of stochastic elements can prevent non-uniqueness and singularities, even with less regular drift conditions. Compare techniques used for deterministic equations with PDE approaches for stochastic cases. Gain insights into the conservation of Sobolev regularity and the restoration of uniqueness in stochastic transport equations. Learn about the Ladyzhenskaya–Prodi–Serrin condition and its significance in fluid dynamics and equation solvability. Understand the collaborative research efforts behind these findings, involving F. Flandoli, M. Gubinelli, and M. Maurelli.
Syllabus
Lisa Beck: Regularization by noise for the stochastic transport equation
Taught by
Hausdorff Center for Mathematics