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 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 […]

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 July 3, 2024

Clustering in pure-attention hardmax transformers and its role in sentiment analysis

Clustering in pure-attention hardmax transformers and its role in sentiment analysis This post provides an overview of the results in the paper […]

Published July 3, 2023

Reinforcement learning as a new perspective into controlling physical systems

Reinforcement learning as a new perspective into controlling physical systems Introduction Optimal control addresses the problem of bringing a system from 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
  • CIRM Workshop – HYCO: A Hybrid-Cooperative Strategy for Data-Driven PDE Model Learning
  • FAU MoD workshop L. Liverani / H. Holthusen
  • Evaluating client contribution in Federated learning
  • A relaxed splitting method for solving variational inclusion and fixed point problems
  • Workshop on Recent Trends in Applied Mathematics and Machine Learning 2025

©  2019 - 2025  – 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