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Found 3 papers, 2 papers with code
Implementation and (Inverse Modified) Error Analysis for implicitly-templated ODE-nets
We thus formulate an adaptive algorithm which monitors the level of error and adapts the number of (unrolled) implicit solution iterations during the training process, so that the error of the unrolled approximation is less than the current learning loss.
On Numerical Integration in Neural Ordinary Differential Equations
The combination of ordinary differential equations and neural networks, i. e., neural ordinary differential equations (Neural ODE), has been widely studied from various angles.
VPNets: Volume-preserving neural networks for learning source-free dynamics
We propose volume-preserving networks (VPNets) for learning unknown source-free dynamical systems using trajectory data.
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