On Geometry Regularization in Autoencoder Reduced-Order Models with Latent Neural ODE Dynamics

arXiv:2603.03238v1 Announce Type: cross Abstract: We investigate geometric regularization strategies for learned latent representations in encoder--decoder reduced-order models. In a fixed experimental setting for the advection--diffusion--reaction (ADR) equation, we model lat...

🔗 Read more: https://arxiv.org/abs/2603.03238

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