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This project provides a novel combination of the field of differential algebraic equations and deep neural networks, and this combination enables us to add constraints to neural networks. We explore various constraint methods and compare their strengths and weaknesses.

License: MIT License

Python 100.00%
constraints differential-algebraic-equations neural-network

constrained-neural-networks's Introduction

Hi! I'm Tue Boesen.

I am a machine learning scientist and have previously worked as: software developer, researcher, project lead, and technical advisor/consultant on various projects. I have a solid foundation in: physics, mathematics, data science, and high-performance-computing. I am familiar with programming best practices and generating production-ready code. Within machine learning, I have specialized in physics-informed and graph neural networks, but I have experience with most areas of deep learning, and I have applied machine learning in many different fields.

My CV can be found here.

To get in contact with me, please send an email to [email protected].

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