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Learning Port Hamiltonian Structures Using PINNs Architecture

Offered By: Fields Institute via YouTube

Tags

Machine Learning Courses Dynamical Systems Courses Neural Network Architecture Courses Physics Informed Neural Networks Courses

Course Description

Overview

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Explore the intersection of machine learning and dynamical systems in this 30-minute conference talk by Karim Cherifi from TU Berlin. Delve into the application of Physics-Informed Neural Networks (PINNs) architecture for learning Port Hamiltonian structures, a powerful framework for modeling complex physical systems. Gain insights into cutting-edge research presented at the Fourth Symposium on Machine Learning and Dynamical Systems, hosted by the Fields Institute.

Syllabus

Learning Port Hamiltonian structures using PINNs type architecture


Taught by

Fields Institute

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