Tuesday, 28 October 2025

17:00 - 18:00

UniDistance Suisse & online, Schinerstrasse 18, 3900 Brig

We will demonstrate how ideas from kernel interpolation can be extended for use as a tool to understand the geometry of point clouds and perform analysis for functions defined on it. Reformulating the relevant interpolation problems as optimization problems also suggests natural a natural regularization that proves effective when the data is noisy. The regularization parameter admits a probabilistic interpretation that clarifies its meaning. Numerical experiments will be presented.

Speaker

Prof. Patrick Guidotti is a Swiss‐born mathematician who is a Professor in the Department of Mathematics at the University of California, Irvine. He earned his Ph.D. from the University of Zurich in 1996. Before joining UCI in Fall 2001, he held a Swiss National Science Foundation postdoctoral fellowship, including stints in Germany (Martin‐Luther University Halle‐Wittenberg) and as a Von Kármán Instructor at Caltech. His research encompasses analysis, partial differential equations (both elliptic and parabolic types), and applications in applied and computational mathematics.