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Proceedings of Machine Learning Research | Proceedings of the 1st ECAI Workshop on “Machine Learning Meets Differential Equations: From Theory to Applications” Held in Santiago de Compostela, Spain on 20 October 2024 Published as Volume 255 by the Proceedings of Machine Learning Research on 06 October 2024. Volume Edited by: Cecı́lia Coelho Bernd Zimmering M. Fernanda P. Costa Luı́s L. Ferrás Oliver Niggemann Series Editors: Neil D. Lawrence
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Volume 255: 1st ECAI Workshop on “Machine Learning Meets Differential Equations: From Theory to Applications”, 20 October 2024, Santiago de Compostela, Spain

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Editors: Cecı́lia Coelho, Bernd Zimmering, M. Fernanda P. Costa, Luı́s L. Ferrás, Oliver Niggemann

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Optimising Neural Fractional Differential Equations for Performance and Efficiency

Bernd Zimmering, Cecília Coelho, Oliver Niggemann; Proceedings of the 1st ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 255:1-22

Neural-based models ensemble for identification of the vibrating beam system

Krzysztof Patan, Maciej Patan, Piotr Balik; Proceedings of the 1st ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 255:1-13

Time and State Dependent Neural Delay Differential Equations

Thibault Monsel, Onofrio Semeraro, Lionel Mathelin, Guillaume Charpiat; Proceedings of the 1st ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 255:1-20

Accelerating Hopfield Network Dynamics: Beyond Synchronous Updates and Forward Euler

Cédric Goemaere, Johannes Deleu, Thomas Demeester; Proceedings of the 1st ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 255:1-21

A Neural Ordinary Differential Equations Approach for 2D Flow Properties Analysis of Hydraulic Structures

Sebastian Eilermann, Lisa Lüddecke, Michael Hohmann, Bernd Zimmering, Mario Oertel, Oliver Niggemann; Proceedings of the 1st ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 255:1-17

PINNtegrate: PINN-based Integral-Learning for Variational and Interface Problems

Frank Ehebrecht, Toni Scharle, Martin Atzmueller; Proceedings of the 1st ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 255:1-16

What happens to diffusion model likelihood when your model is conditional?

Mattias Cross, Anton Ragni; Proceedings of the 1st ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 255:1-14

Optimal Control of a Coastal Ecosystem Through Neural Ordinary Differential Equations

Cecília Coelho, Fernanda Costa, Luís Ferrás; Proceedings of the 1st ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 255:1-9

EMILY: Extracting sparse Model from ImpLicit dYnamics

Ayan Banerjee, Sandeep Gupta; Proceedings of the 1st ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 255:1-11

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