Skip to content
Back Home
  • Home
  • The Chair
    • About
    • Our Head
    • Our Team
    • Contact
    • Past Members
  • Research
    • Publications
    • Projects
    • Teaching
    • Initiatives
    • Posts on Math and Research
    • Contributors
  • Join us!
    • Careers
    • Events
    • Past Events
  • Resources
    • Seminars / Lectures
    • Math to go!
    • Academy
    • GitHub
  • Search
Back Home
  • Search
  • Home
  • The Chair
    • About
    • Our Head
    • Our Team
    • Contact
    • Past Members
  • Research
    • Publications
    • Projects
    • Teaching
    • Initiatives
    • Posts on Math and Research
    • Contributors
  • Join us!
    • Careers
    • Events
    • Past Events
  • Resources
    • Seminars / Lectures
    • Math to go!
    • Academy
    • GitHub

Robust neural ODEs

Published June 20, 2022

The code implements the gradient regularization method of robust training in the setting of neural ODEs.
Various jupyter notebooks are included that generate plots comparing standard to robust training for 2d point clouds.

Code:

A good starting point is robustness_plots.ipynb

Code is based on GitHub: borjanG : 2021-dynamical-systems that uses the torchdiffeq package GitHub : rtqichen: torchdiffeq

 

|| Go to the Math & Research main page

You may also like

Published December 1, 2023

PINNs Introductory Code for the Heat Equation

PINNs Introductory Code for the Heat Equation This repository provides some basic insights on Physics Informed Neural Networks (PINNs) and their implementation. […]

Published July 30, 2022

Sheep Herding Game

Author: Daniël Veldman, FAU DCN-AvH Code: A sheep herding game in MATLAB developed for the Long Night of Science #NdW22 (Lange Nacht […]

Published August 5, 2022

Gas networks at stationary states: Analysis, software and visualization

Gas networks at stationary states: Analysis, software and visualization Code: Files to run: nocircle.m, onecircle.m or twocircles.m   1 Introduction This post […]

Published August 4, 2023

Combined convection and diffusion in a network. A numerical analysis

Combined convection and diffusion in a network. A numerical analysis. The problem: a contaminant in a network of water pipes Imagine that […]

Post navigation

  • Previous post Optimal design of sensors and actuators by E. Zuazua
  • Back to post list
  • Next post Mini-workshop: “Recent Advances in Analysis and Control”
Last news
  • From Optimal Control to Reinforcement Learning: A Motivating Example from the Perspective of Linear Quadratic Regulators
  • Enrique Zuazua invited to deliver a Special Section Lecture at ICM 2026
  • PhD Thesis defense by A. Alvarez-Lopez
  • MLPDES26, Machine Learning and PDEs Workshop (2026)
  • FAU MoD Lecture: Reverse typography and the theory of shape: Can old books be brought back to life?

©  2019 - 2026  – All rights reserved - FAU DCN-AvH Chair for Dynamics, Control and Numerics - Alexander von Humboldt Professorship at Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany Imprint | Privacy | Accessibility | Contact