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Sparse Spectral Methods for Power-Law Interactions
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Classroom Contents
Mathématiques Appliquées - Neural Networks, Optimization, and Deep Learning
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- 1 Bruno Després: Neural Networks from the viewpoint of Numerical Analysis
- 2 Soledad Villar: Units-equivariant machine learning
- 3 Tom Trogdon: Perturbations of orthogonal polynomials: Riemann-Hilbert problems, random matrices ...
- 4 Sebastien Le Digabel: Blackbox optimization with the MADS algorithm and the NOMAD software
- 5 Fabian Pedregosa: Efficient and Modular Implicit Differentiation
- 6 David Rolnick: Expressivity and learnability in deep neural networks
- 7 Matus Benko: Variational Analysis: Basics, Calculus, and Semismoothness*
- 8 Alex Bihlo: Deep neural networks for solving differential equations on general orientable surface
- 9 Degenerate singular cycles and chaotic switching in the two-site open Bose--Hubbard model
- 10 Equidistant and non equidistant pulsing patterns in an excitable microlaser with delayed feedback
- 11 Deep learning of conjugate mappings
- 12 Hidden convexity in nonconvex optimization
- 13 Les mathématiques ont une histoire et une géographie
- 14 Experimental continuation of nonlinear load-bearing structures
- 15 Algorithms for Deterministically Constrained Stochastic Optimization
- 16 Some Thoughts on Physics Informed Neural Networks
- 17 On LASSO parameter sensitivity
- 18 The Modern Mathematics of Deep Learning
- 19 Nonlinear reduced models for parametric PDEs
- 20 Mathematical Foundations of Robust and Distributionally Robust Optimization
- 21 From differential equations to deep learning for image analysis
- 22 Depth-Adaptive Neural Networks from the Optimal Control viewpoint
- 23 Signal Recovery with Generative Priors
- 24 Targeted use of deep learning for physics and engineering
- 25 Rayleigh quotient optimizations and eigenvalue problems
- 26 Optimal approximation for unconstrained non-submodular minimization
- 27 Halting Time is Predictable for Large Models: A Universality Property and Average-case Analysis
- 28 Parallel-in-time numerical solution of time-dependent PDEs
- 29 A Primal-Dual Algorithm for Risk Minimization in PDE-Constrained Optimization
- 30 Optimality in Optimization
- 31 Variational Perspectives on Mathematical Optimization
- 32 Sparse Spectral Methods for Power-Law Interactions
- 33 Optimization on Spheres : Models and Proximal Algorithms with Computational Performance Comparisons
- 34 Algorithmic stability for generalization guarantees in machine learning
- 35 Simple agent-based models and their continuum limit
- 36 Data-driven supervised learning: Neural networks and uncertainty quantification
- 37 Videoconference: Detecting and distinguishing bifurcations from noisy time series data
- 38 Videoconference: The Ultraspherical Spectral Method
