jeudi 26 mars 2026, 12:15 → 13:15

Orateur : Sébastien Gerchinovitz (IRT Saint-Exupéry)

Title: An introduction to conformal prediction

Abstract: Recent achievements in deep learning have shown great empirical performances for multiple learning tasks in computer vision, natural language processing, scientific discovery, and more. However, deep learning models are known to fail, so that quantifying their errors in a statistically rigorous way is key for high-stakes applications. This talk is an introduction to conformal prediction, a set of simple yet generic statistical methods towards that goal. We will present one classical method, how to analyze it through simple symmetry arguments, as well as some limitations, extensions, and an application to computer vision.

https://indico.math.cnrs.fr/event/16300/

jeudi 2 avr. 2026, 12:15 → 13:15

Orateur : Radu Ignat (IMT)

Title : Vortex analysis in variational models.

Abstract: Vortices are topological singularities that appear in many physical systems (superconductivity, superfluids, ferromagnetics, liquid crystals etc.) We will present the analysis of vortices in a two dimensional Ginzburg-Landau (GL) model that is the prototype in several variational problems. This toy model depends on a small parameter epsilon and it is related to the harmonic map problem for unit length vector fields as epsilon tends to 0.
We will study ground states of (GL) for a given boundary data that carries a topological charge and induces the nucleation of vortices. Several mathematical tools will be introduced for this study such as the topological degree, the jacobian of the ground state (detecting the vortices) as well as the renormalized energy between vortices (determining their optimal location). 

https://indico.math.cnrs.fr/event/16301/