Autoencoders enable nonlinear dimensionality reduction for parametric ODEs, with analysis of exact representation properties and convergence of the reduced model to the original.
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Local energy minimizers for binary-star systems in the Wasserstein L^∞ topology possess gradients, L^∞ neighborhoods, and finite energy, unlike in standard topological vector space topologies.
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Model reduction of parametric ordinary differential equations via autoencoders: representation properties and convergence analysis
Autoencoders enable nonlinear dimensionality reduction for parametric ODEs, with analysis of exact representation properties and convergence of the reduced model to the original.
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Gradient Existence and Energy Finiteness of Local Minimizers in the Wasserstein $L^\infty$ Topology for Binary-Star Systems
Local energy minimizers for binary-star systems in the Wasserstein L^∞ topology possess gradients, L^∞ neighborhoods, and finite energy, unlike in standard topological vector space topologies.