Tutorials / Mini-Courses
High-Dimensional Approximation.
Research School on Uncertainty in Scientific Computing (ETICS), Golfe de Lozari (L'Ile Rousse), France, October 2-7, 2022.
High-Dimensional Approximation and Approximation Theory of tensor networks.
Journees du GDR MANU, Le Croisic, October 25-26, 2021.
Approximation and learning with tree tensor networks.
CEMRACS 2021 on Data Assimilation and Reduced Modeling for High Dimensional Problems, CIRM, Luminy, July 19-23, 2021.
Deep tensor networks.
Workshop Learning and simulation in high dimension, Airbus Group, Paris, June 25-27, 2019.
Polynomial, sparse and low-rank approximations.
RICAM Special Semester on “Multivariate Algorithms and their Foundations in Number Theory”, Workshop Frontier Technologies for High-Dimensional Problems and Uncertainty Quantification, Linz, 14-21 December, 2018.Linz, 2018.
Approximation with tree tensor networks.
Model Order Reduction Summer School 2019, Eindhoven, Sep. 23-27, 2019.
A brief introduction to Randomized Linear Algebra.
Model Order Reduction Summer School 2019, Eindhoven, Sep. 23-27, 2019.
Low-rank and sparse methods for high-dimensional approximation and model order reduction.
Summer school CEA/EDF/INRIA, 20-24 June, 2016.
Tensor numerical methods for high-dimensional problems.
Journees du GDR AMORE, IHP, Paris, December 2019.
Tensor numerical methods for high-dimensional problems.
IHP quarter on Numerical Methods for PDEs, Cargese, September 5-9, 2016.
Low-rank tensor methods for parametric and stochastic problems.
Oberwolfach Seminar: Projection Based Model Reduction: Reduced Basis Methods, Proper Orthogonal Decomposition, and Low Rank Tensor Approximations, Oberwolfach, 23 Nov - 29 Nov, 2014.