Philippe von Wurstemberger

According to our database1, Philippe von Wurstemberger authored at least 11 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Physics-informed diffusion models in spectral space.
CoRR, February, 2026

2025
Adam symmetry theorem: characterization of the convergence of the stochastic Adam optimizer.
CoRR, November, 2025

2024
An overview of diffusion models for generative artificial intelligence.
CoRR, 2024

An Overview on Machine Learning Methods for Partial Differential Equations: from Physics Informed Neural Networks to Deep Operator Learning.
CoRR, 2024

2023
Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory.
CoRR, 2023

Algorithmically Designed Artificial Neural Networks (ADANNs): Higher order deep operator learning for parametric partial differential equations.
CoRR, 2023

2022
Learning the random variables in Monte Carlo simulations with stochastic gradient descent: Machine learning for parametric PDEs and financial derivative pricing.
CoRR, 2022

2020
Lower error bounds for the stochastic gradient descent optimization algorithm: Sharp convergence rates for slowly and fast decaying learning rates.
J. Complex., 2020

High-dimensional approximation spaces of artificial neural networks and applications to partial differential equations.
CoRR, 2020

Numerical simulations for full history recursive multilevel Picard approximations for systems of high-dimensional partial differential equations.
CoRR, 2020

2018
A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations.
CoRR, 2018


  Loading...