Showing 1–20 of 38 results
/ Date/ Name
Apr 13, 2005Equation-free, multiscale computation for unsteady random diffusionOct 15, 2019Data-Driven Deep Learning of Partial Differential Equations in Modal SpaceJun 3, 2022Learning Fine Scale Dynamics from Coarse Observations via Inner RecurrenceDec 15, 2023Modeling Unknown Stochastic Dynamical System via AutoencoderOct 23, 2024Deep learning for model correction of dynamical systems with data scarcityJun 22, 2024Modeling Unknown Stochastic Dynamical System Subject to External ExcitationApr 2, 2025Multi-fidelity Parameter Estimation Using Conditional Diffusion ModelsMar 21, 2026Predictability of Observables of Dynamical SystemsJul 20, 2023Flow Map Learning for Unknown Dynamical Systems: Overview, Implementation, and BenchmarksFeb 11, 2020A Non-Intrusive Correction Algorithm for Classification Problems with Corrupted DataJun 2, 2020Data-driven learning of non-autonomous systemsMar 7, 2022Robust Modeling of Unknown Dynamical Systems via Ensemble Averaged LearningOct 4, 2024A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical SystemsSep 27, 2024Chebyshev Feature Neural Network for Accurate Function ApproximationJun 23, 2025Exact Conditional Score-Guided Generative Modeling for Amortized Inference in Uncertainty QuantificationMar 8, 2026Numerical Approach for On-the-Fly Active Flow Control via Flow Map Learning MethodMay 22, 2018Reducing Parameter Space for Neural Network TrainingNov 13, 2018Data Driven Governing Equations Approximation Using Deep Neural NetworksMay 10, 2018Energy Conserving Galerkin Approximation of Two Dimensional Wave Equations with Random CoefficientsAug 22, 2018An Explicit Neural Network Construction for Piecewise Constant Function Approximation