Different architectures for neural ordinary differential equations
Author:   Elias Walder
Publisher:   LAP Lambert Academic Publishing
ISBN:  

9786207486434


Pages:   96
Publication Date:   17 July 2025
Format:   Paperback
Availability:   Available To Order   Availability explained
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Different architectures for neural ordinary differential equations


Overview

Machine learning has been getting more and more important during the last decades. One of the most important tools in machine learning are neural networks. A rather modern approach of constructing a neural network is using a neural ordinary differential equation (or neural ODE). Here, the idea is to construct a neural network which can be evaluated by (numerically) solving an ODE. Neural ODEs are a powerful tool to solve many different machine learning problems. However, it is not so easy to construct a fitting neural ODE model in practice. In the thesis, some basic ways of constructing a neural ODE are explored.

Full Product Details

Author:   Elias Walder
Publisher:   LAP Lambert Academic Publishing
Imprint:   LAP Lambert Academic Publishing
Dimensions:   Width: 15.20cm , Height: 0.60cm , Length: 22.90cm
Weight:   0.141kg
ISBN:  

9786207486434


ISBN 10:   6207486439
Pages:   96
Publication Date:   17 July 2025
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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