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cs.LG2024
Learnable & Interpretable Model Combination in Dynamical Systems Modeling
Tobias Thummerer, Lars Mikelsons
During modeling of dynamical systems, often two or more model architectures are combined to obtain a more powerful or efficient model regarding a specific application area. This co…
cs.LG2023★ 4 cited
Eigen-informed NeuralODEs: Dealing with stability and convergence issues of NeuralODEs
Tobias Thummerer, Lars Mikelsons
Using vanilla NeuralODEs to model large and/or complex systems often fails due two reasons: Stability and convergence. NeuralODEs are capable of describing stable as well as instab…
cs.LG2022★ 1 cited
NeuralFMU: Presenting a workflow for integrating hybrid NeuralODEs into real world applications
Tobias Thummerer, Johannes Stoljar, Lars Mikelsons
The term NeuralODE describes the structural combination of an Artifical Neural Network (ANN) and a numerical solver for Ordinary Differential Equations (ODEs), the former acts as t…