Showing 1–18 of 18 results
/ Date/ Name
Sep 25, 2022Error analysis based on inverse modified differential equations for discovery of dynamics using linear multistep methods and deep learningDec 23, 2019Unit triangular factorization of the matrix symplectic groupApr 29, 2022VPNets: Volume-preserving neural networks for learning source-free dynamicsApr 23, 2020Deep Hamiltonian networks based on symplectic integratorsJun 21, 2021Approximation capabilities of measure-preserving neural networksMar 7, 2022Convergence of physics-informed neural networks applied to linear second-order elliptic interface problemsAug 28, 2023Solving parametric elliptic interface problems via interfaced operator networkFeb 22, 2024DynGMA: a robust approach for learning stochastic differential equations from dataJun 15, 2022On Numerical Integration in Neural Ordinary Differential EquationsSep 2, 2020Inverse modified differential equations for discovery of dynamicsFeb 2, 2025Continuity-Preserving Convolutional Autoencoders for Learning Continuous Latent Dynamical Models from ImagesAug 8, 2022Explicit K-symplectic methods for nonseparable non-canonical Hamiltonian systemsMay 11, 2022Poisson Integrators based on splitting method for Poisson systemsOct 28, 2025Identifiable learning of dissipative dynamicsJan 11, 2020SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systemsApr 21, 2023Effective Numerical Simulations of Synchronous Generator SystemMar 31, 2023Implementation and (Inverse Modified) Error Analysis for implicitly-templated ODE-netsMay 5, 2026Calculating Domain of Attraction Boundary of Power Systems Based on the Gentlest Ascent Dynamics