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David Barajas-Solano

Randomized Physics-Informed Neural Networks for Bayesian Data Assimilation

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Jul 05, 2024
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Randomized Physics-Informed Machine Learning for Uncertainty Quantification in High-Dimensional Inverse Problems

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Dec 23, 2023
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Online Real-time Learning of Dynamical Systems from Noisy Streaming Data

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Dec 10, 2022
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Dynamic mode decomposition for forecasting and analysis of power grid load data

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Oct 08, 2020
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Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs

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Oct 29, 2019
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Electric Load and Power Forecasting Using Ensemble Gaussian Process Regression

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Oct 09, 2019
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Physics-Informed CoKriging: A Gaussian-Process-Regression-Based Multifidelity Method for Data-Model Convergence

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Nov 24, 2018
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