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Parcours 2021 - 2022

Advanced mathematics 2nd year 2021-2022


Courses are organized in thematic programs, and there will be three such programs in 2021-2022. Courses will start in mid September. However, some of the programs will offer refresher courses, that will start during the week of August 30th. The following three programs will be offered.

Groups, Geometry, Dynamics and Model Theory


Detailed program here.

Basic courses (3 out of 4x24h):

Introduction to ergodic theory and topological dynamics (Damien Gaboriau, Adrien Le Boudec)
Lie groups and Lie algebras (Sophie Morel, Bruno Sévennec)
Geometric group theory (Jean-Claude Sikorav)
Model theory and its applications (Itaï Ben Yaacov)

Advanced courses (3 out of 4x24h):

Amenability and dynamics (Nicolás Matte Bon, Todor Tsankov)
Lattices in semisimple Lie groups (Amine Marrakchi, Mikael de la Salle)
Actions on trees and the elementary theory of free groups (Abderezak Ould Houcine)
Model theory of groups (Frank Wagner)

 

Partial Differential Equations and Applications


Detailed program here.

Refresher courses (3x16h):

Basic tools of functional analysis (Simon Masnou)
Stochastic tools (Grégory Miermont)
Starting with PDEs (Francesco Fanelli)
 
Basic courses (3x24h):
 
Evolution equations (Emmanuel Grenier)
Calculus of variations and elliptic equations (Filippo Santambrogio)
Discontinuous finite-element methods and applications (Daniel Le Roux)
 
Advanced courses (4x18h):
 
Stochastic PDEs and their asymptotic behaviour (Alexandre Boritchev)
Many-body quantum mechanics and mean-field limits (Nicolas Rougerie)
Optimal transport theory and links with parabolic equations (Ivan Gentil)
Numerical approximation methods for fluid mechanics (Khaled Saleh)
 

Probability and statistics


Detailed program here.

Refresher courses (3x16h):

Basic tools of functional analysis (Simon Masnou)
Stochastic tools (Grégory Miermont)
Starting with PDEs (Francesco Fanelli)
 
Basic courses (3 out of 4x24h):
 
Concentration of measure in probability and high-dimensional statistical learning (Guillaume Aubrun, Aurélien Garivier, Rémi Gribonval)
Non-parametrics (Irène Gannaz, Clément Marteau, Franck Picard)
Stochastic calculus (Grégory Miermont)
Statistical physics (Christophe Garban)
 
Advanced courses (4 out of 6x18h):
 
Large random matrices and applications (Alice Guionnet)
Determinantal processes (Adrien Kassel)
Random graphs (Dieter Mitsche)
Mathematical foundations of deep neural networks (Aurélien Garivier, Rémi Gribonval, Nelly Pustelnik)
Inverse problems and high dimension (Yohann de Castro, Rémi Gribonval)
Advanced machine learning theory (Laurent Jacob, Antoine Chambaz)

 

contacts

Responsable du MA2 :

Nicolas Rougerie
ENS, site Monod, bâtiment GN1 (l’arche), 4e étage

Gestionnaires de scolarité

École normale supérieure

Sophie Bonche
Site Monod, bâtiment LE (accolé au GN1, côté nord de l’allée d’Italie)
bureau 536, allée Allan C. Wilson
04.72.72.85.53

Université Claude Bernard

Delphine Jouve
04.72.44.85.53
delphine.jouve@univ-lyon1.fr

Contact

ENS de Lyon
15 parvis René Descartes - BP 7000
69342 Lyon Cedex 07 - FRANCE
Tél. : Site René Descartes (siège) : +33 (0) 4 37 37 60 00
Site Jacques Monod : +33 (0) 4 72 72 80 00

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