Goal-conditioned neural ODEs built from bi-Lipschitz diffeomorphisms deliver global exponential stability and safe-set invariance for all-pairs motion planning with explicit convergence bounds.
Geometrization of 3-manifolds via the Ricci flow
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Goal-Conditioned Neural ODEs with Guaranteed Safety and Stability for Learning-Based All-Pairs Motion Planning
Goal-conditioned neural ODEs built from bi-Lipschitz diffeomorphisms deliver global exponential stability and safe-set invariance for all-pairs motion planning with explicit convergence bounds.