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Electric Load and Power Forecasting Using Ensemble Gaussian Process Regression., , , , and . CoRR, (2019)Physics-Informed Kriging: A Physics-Informed Gaussian Process Regression Method for Data-Model Convergence., , and . CoRR, (2018)Enforcing constraints for interpolation and extrapolation in Generative Adversarial Networks., , , and . CoRR, (2018)Stochastic Basis Adaptation and Spatial Domain Decomposition for Partial Differential Equations with Random Coefficients., , and . SIAM/ASA J. Uncertain. Quantification, 6 (1): 273-301 (2018)Physics-Informed Gaussian Process Regression for Probabilistic States Estimation and Forecasting in Power Grids., , , and . CoRR, (2020)Discrete Models of Fluids: Spatial Averaging, Closure, and Model Reduction., , and . SIAM J. Appl. Math., 74 (2): 477-515 (2014)Stochastically Forced Ensemble Dynamic Mode Decomposition for Forecasting and Analysis of Near-Periodic Systems., , , , and . IEEE Access, (2022)Physics-Informed Neural Network Method for Parabolic Differential Equations with Sharply Perturbed Initial Conditions., , and . CoRR, (2022)Physics-informed CoKriging model of a redox flow battery., and . CoRR, (2021)Time-dependent stochastic basis adaptation for uncertainty quantification., , and . CoRR, (2021)