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Ling Guo

Energy based diffusion generator for efficient sampling of Boltzmann distributions

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Jan 04, 2024
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IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning

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Feb 07, 2023
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Monte Carlo PINNs: deep learning approach for forward and inverse problems involving high dimensional fractional partial differential equations

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Mar 16, 2022
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Uncertainty Quantification in Scientific Machine Learning: Methods, Metrics, and Comparisons

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Jan 19, 2022
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Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models

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Sep 07, 2021
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Removable and/or Repeated Units Emerge in Overparametrized Deep Neural Networks

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Dec 21, 2019
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Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks

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May 03, 2019
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I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences

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Apr 16, 2019
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Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems

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Sep 21, 2018
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