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

Training of neural ODEs using pyTorch

Published September 13, 2022

Start with tutorials to get familiar with the code
Tutorial 1: Train a neural ODE based network on point cloud data set and generating a gif of the resulting time evolution of the neural ODE

Code:

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

 

Code:

|| Go to the Math & Research main page

You may also like

Published November 14, 2025

Sentiment Analysis with Transformers

Sentiment Analysis with Transformers This post includes an app SentimentAnalysisTransformersApp created for a public outreach activity organized by the Chair for Dynamics, […]

Published September 30, 2022

Approximating the 1D wave equation using Physics Informed Neural Networks (PINNs)

Approximating the 1D wave equation using Physics Informed Neural Networks (PINNs)   Introduction Accurate and fast predictions of numerical solutions are of […]

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 […]

Published December 20, 2022

Federated Learning: Protect your data and privacy

Federated Learning: Protect your data and privacy Code: A basic PyTorch implementation of the FedAvg algorithm (GitHub) Federated Learning is becoming an […]

Post navigation

  • Previous post Course: A Practical Introduction to Control, Numerics, and Machine Learning (IFAC CPDE 2022)
  • Back to post list
  • Next post FAU MoD Lecture: Learning-Based Optimization and PDE Control in User-Assignable Finite Time
Last news
  • 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?
  • Sums-of-squares Polyconvexity
  • Enrique Zuazua invited to deliver a Special Section Lecture at ICM 2026
  • EZ 65: Control, PDEs and Machine Learning

©  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