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Editors: Cecı́lia Coelho, Bernd Zimmering, M. Fernanda P. Costa, Luı́s L. Ferrás, Oliver Niggemann
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Learning non-Markovian Dynamical Systems with Signature-based Encoders
; Proceedings of the 2nd ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 277:1-25
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TaylorNet: Learning PDEs from Non-Grid Data
Andrzej Dulny, Paul Heinisch, Andreas Hotho, Anna Krause; Proceedings of the 2nd ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 277:26-46
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Physics-Informed Graph Neural Networks for Air Pollution Forecasting in the Netherlands
Nikolas Assiotis, Rachel Hau, Valentijn Oldenburg, Rik Verbiest, Julian Koellermeier, Matthia Sabatelli, Juan Cardenas-Cartagena; Proceedings of the 2nd ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 277:47-70
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A Unified Framework for Neural Computation and Learning Over Time
Stefano Melacci, Alessandro Betti, Michele Casoni, Tommaso Guidi, Matteo Tiezzi, Marco Gori; Proceedings of the 2nd ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 277:71-95
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ExtremONet: Extreme-Learning-based Neural Operator for identifying dynamical systems
Jari Beysen, Floriano Tori; Proceedings of the 2nd ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 277:96-120
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Flowing Straighter with Conditional Flow Matching for Accurate Speech Enhancement
Mattias Cross, Anton Ragni; Proceedings of the 2nd ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 277:121-132
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Hamiltonian Normalizing Flows as kinetic PDE solvers: application to the 1D Vlasov-Poisson Equations
Vincent Souveton, Sébastien Terrana; Proceedings of the 2nd ECAI Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications", PMLR 277:133-146
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