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Thomas O'Leary-Roseberry

Fast Unconstrained Optimization via Hessian Averaging and Adaptive Gradient Sampling Methods

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Aug 14, 2024
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Efficient geometric Markov chain Monte Carlo for nonlinear Bayesian inversion enabled by derivative-informed neural operators

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Mar 13, 2024
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Efficient PDE-Constrained optimization under high-dimensional uncertainty using derivative-informed neural operators

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May 31, 2023
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Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems

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Oct 06, 2022
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Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning

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Jun 23, 2022
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Adaptive Projected Residual Networks for Learning Parametric Maps from Sparse Data

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Dec 14, 2021
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Derivative-Informed Projected Neural Networks for High-Dimensional Parametric Maps Governed by PDEs

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Nov 30, 2020
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Ill-Posedness and Optimization Geometry for Nonlinear Neural Network Training

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Feb 07, 2020
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Low Rank Saddle Free Newton: Algorithm and Analysis

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Feb 07, 2020
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