PhD Student
martin.hernandez@fau.de
Room 03.311 | Friedrich-Alexander-Universität Erlangen-Nürnberg. FAU DCN-AvH Chair for Dynamics, Control, Machine Learning and Numerics – Alexander von Humboldt Professorship.
+49 9131 85-67126
Hello! My name is Martin Hernandez Salinas, I am a doctoral student at the Chair for Dynamics, Control, Machine Learning and Numerics – Alexander von Humboldt- Professorship.
I have a degree in mathematical engineering and a master’s degree in mathematical sciences from Universidad Técnica Federico Santa María. My main fields of interest are partial differential equations, control theory, numerical analysis and machine learning.
Master Thesis: Turnpike under uncertainty (April 9th, 2021)
Course: Mathematics 2 (Linear algebra). Theoretical and practical basic subject that provides the fundamental concepts of series, matrix, vector algebra, and basic notions of finite-dimensional spaces. | Universidad Técnica Federico Santa María (July 2021 – December 2021)
Projects
• TRR154
Events
• CIN-PDE 2024 Poster: Multilayer Perceptrons: Multiclassification and Universal Approximation (Martín Hernández, Enrique Zuazua) | see poster. Conference on Control, Inversion and Numerics for PDEs (Oct. 7-10, 2024 at Fudan University, Shanghai)
My posts on Math & Research
PINNs Introductory Code for the Heat Equation
Lloyd’s Algorithm
Uniform Turnpike Property
My posters
Multilayer Perceptrons: Multiclassification and Universal Approximation
Publications
2025
- , :
Deep Neural Networks: Multi-Classification and Universal Approximation
(2025)
URL: https://arxiv.org/abs/2409.06555v1
BibTeX: Download
2024
- , , :
Averaged observations and turnpike phenomenon for parameter-dependent systems
(2024)
BibTeX: Download - , :
Uniform Turnpike Property and Singular Limits
DOI: 10.1007/s10440-024-00640-7
URL: https://link.springer.com/article/10.1007/s10440-024-00640-7
BibTeX: Download
2022
- , , :
AVERAGED TURNPIKE PROPERTY FOR DIFFERENTIAL EQUATIONS WITH RANDOM CONSTANT COEFFICIENTS
In: Mathematical Control and Related Fields (2022)
ISSN: 2156-8472
DOI: 10.3934/mcrf.2022016
BibTeX: Download
