Showing 1–20 of 40 results
/ Date/ Name
Dec 7, 2018When Bifidelity Meets CoKriging: An Efficient Physics-Informed Multifidelity MethodJun 15, 2021Graphical Gaussian Process Regression Model for Aqueous Solvation Free Energy Prediction of Organic Molecules in Redox Flow BatteryMar 19, 2021A Physics-Informed Neural Network Framework For Partial Differential Equations on 3D Surfaces: Time-Dependent ProblemsSep 10, 2018Physics-Information-Aided Kriging: Constructing Covariance Functions using Stochastic Simulation ModelsJul 10, 2017A General Framework for Enhancing Sparsity of Generalized Polynomial Chaos ExpansionsSep 3, 2020Augmented Gaussian Random Field: Theory and ComputationOct 19, 2020A Bayesian Approach for Characterizing and Mitigating Gate and Measurement ErrorsSep 22, 2017Sliced-Inverse-Regression-Aided Rotated Compressive Sensing Method for Uncertainty QuantificationAug 3, 2020Multifidelity Data Fusion via Gradient-Enhanced Gaussian Process RegressionFeb 19, 2022The Adaptive Spectral Koopman Method for Dynamical SystemsNov 7, 2015Elliptic Involution on Knot ComplementsMar 28, 2024An Efficient Quantum Algorithm for Linear System Problem in Tensor FormatDec 12, 2023Unleashed from Constrained Optimization: Quantum Computing for Quantum Chemistry Employing Generator Coordinate Inspired MethodNov 24, 2018Physics-Informed CoKriging: A Gaussian-Process-Regression-Based Multifidelity Method for Data-Model ConvergenceMar 9, 2023Müntz ball polynomials and Müntz spectral-Galerkin methods for singular eigenvalue problemsDec 22, 2023A Gradient-Based Optimization Method Using the Koopman OperatorJan 13, 2021A general framework of rotational sparse approximation in uncertainty quantificationDec 19, 2022Quantum algorithms for generator coordinate methodsAug 24, 2014Quantifying the influence of conformational uncertainty in biomolecular solvationJun 21, 2016Systematic parameter inference in stochastic mesoscopic modeling