Showing 1–20 of 20 results
/ Date/ Name
Mar 21, 2026Predictability of Observables of Dynamical SystemsMar 8, 2026Numerical Approach for On-the-Fly Active Flow Control via Flow Map Learning MethodJun 23, 2025Exact Conditional Score-Guided Generative Modeling for Amortized Inference in Uncertainty QuantificationApr 2, 2025Multi-fidelity Parameter Estimation Using Conditional Diffusion ModelsOct 23, 2024Deep learning for model correction of dynamical systems with data scarcityOct 4, 2024A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical SystemsSep 27, 2024Chebyshev Feature Neural Network for Accurate Function ApproximationJun 22, 2024Modeling Unknown Stochastic Dynamical System Subject to External ExcitationDec 15, 2023Modeling Unknown Stochastic Dynamical System via AutoencoderJul 20, 2023Flow Map Learning for Unknown Dynamical Systems: Overview, Implementation, and BenchmarksJun 3, 2022Learning Fine Scale Dynamics from Coarse Observations via Inner RecurrenceMar 7, 2022Robust Modeling of Unknown Dynamical Systems via Ensemble Averaged LearningJun 2, 2020Data-driven learning of non-autonomous systemsFeb 11, 2020A Non-Intrusive Correction Algorithm for Classification Problems with Corrupted DataOct 15, 2019Data-Driven Deep Learning of Partial Differential Equations in Modal SpaceNov 13, 2018Data Driven Governing Equations Approximation Using Deep Neural NetworksAug 22, 2018An Explicit Neural Network Construction for Piecewise Constant Function ApproximationMay 22, 2018Reducing Parameter Space for Neural Network TrainingMay 10, 2018Energy Conserving Galerkin Approximation of Two Dimensional Wave Equations with Random CoefficientsApr 13, 2005Equation-free, multiscale computation for unsteady random diffusion