Statistical Inverse Problems and PDEs: Progress and Challenges

Statistical Inverse Problems and PDEs: Progress and Challenges

Explore statistical inverse problems and partial differential equations (PDEs) in this 43-minute lecture by Richard Nickl for the International Mathematical Union. Delve into topics such as inverse regression models, PDE model examples, and challenges in inversion. Examine Bayesian inverse problems, including computation using gradient-based MCMC and Gaussian process priors. Investigate mathematical guarantees for algorithms, focusing on posterior consistency with GPS and computation in high dimensions. Learn about proof ideas and the hardness of cold-start MCMC. Gain insights into the progress made and ongoing challenges in this field of mathematical research.