Derives computable two-sided a posteriori error bounds for PINN approximations of ODEs using localized strong monotonicity for lower bounds and one-sided Lipschitz for upper bounds.
and Ratiu, Tudor S
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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A fully discrete strain-based model for continuum robot dynamics via Lie group variational integrators, combined with an EKF-based observer for states and disturbances, validated on hardware.
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Reliable Error Estimation for PINNs: Lower and Upper A Posteriori Bounds
Derives computable two-sided a posteriori error bounds for PINN approximations of ODEs using localized strong monotonicity for lower bounds and one-sided Lipschitz for upper bounds.
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Discrete Geometric Modeling and Extended State Estimation of Continuum Robots
A fully discrete strain-based model for continuum robot dynamics via Lie group variational integrators, combined with an EKF-based observer for states and disturbances, validated on hardware.