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Stay flexible, get lucky: nonlinear approximation and random sampling meet scientific machine learning
Stay flexible, get lucky: nonlinear approximation and random sampling meet scientific machine learning
SISSA mathLab Seminar
Scuola Superiore di Studi Avanzati (SISSA), Trieste, Italy. October 1st, 2025.
Practical existence theorems for deep learning approximation in high dimensions
Practical existence theorems for deep learning approximation in high dimensions
BIRS workshop, Structured Machine Learning and Time–Stepping for Dynamical Systems (24w5301)
Banff International Research Station (BIRS) for Mathematical Innovation and Discovery. Banff, AB, Canada. February 19, 2024.
The mathematical foundations of deep learning: from rating impossibility to practical existence theorems
The mathematical foundations of deep learning: from rating impossibility to practical existence theorems
One World Seminar Series on the Mathematics of Machine Learning
Online. November 16, 2022.
The curse of dimensionality and the blessings of sparsity and Monte Carlo sampling
The curse of dimensionality and the blessings of sparsity and Monte Carlo sampling
One World Mathematics of INformation, Data, and Signals (1W-MINDS) Seminar
Online. May 13, 2021.
Compressive Sensing Approaches for High-Dimensional Function Approximation
Compressive Sensing Approaches for High-Dimensional Function Approximation
DASIV Spring School Models and Data.
University of South Carolina. Columbia, SC, USA. March 20, 2019.
Sparse High-dimensional Approximation from Highly Noisy Data
Sparse High-dimensional Approximation from Highly Noisy Data
BIRS workshop, 18w5172: Numerical Analysis and Approximation Theory meets Data Science
Banff International Research Station (BIRS) for Mathematical Innovation and Discovery. Banff, AB, Canada. April 22, 2018.
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