Thomas O’Leary-Roseberry

Derivative-informed projected neural networks for high-dimensional parametric maps governed by PDEs

Thomas O’Leary-Roseberry, Umberto Villa, Peng Chen et al. · Computer Methods in Applied Mechanics and Engineering · 2021 · 52 citations · Full text

Computing, Computational Engineering, Mathematics +14

Learning high-dimensional parametric maps via reduced basis adaptive residual networks

Thomas O’Leary-Roseberry, Xiaosong Du, Anirban Chaudhuri et al. · Computer Methods in Applied Mechanics and Engineering · 2022 · 29 citations · Full text

Computing, Computer Science, Machine Learning +8

Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems

Lianghao Cao, Thomas O’Leary-Roseberry, Prashant K. Jha et al. · Journal of Computational Physics · 2023 · 29 citations · Full text

Computing, Computational Engineering, Bayesian Data Analysis +13

Derivative-Informed Neural Operator: An efficient framework for high-dimensional parametric derivative learning

Thomas O’Leary-Roseberry, Peng Chen, Umberto Villa et al. · Journal of Computational Physics · 2023 · 25 citations · Full text

Computing, Mathematics, Derivatives +13

Large-Scale Bayesian Optimal Experimental Design with Derivative-Informed Projected Neural Network

Keyi Wu, Thomas O’Leary-Roseberry, Peng Chen et al. · Journal of Scientific Computing · 2023 · 24 citations

Computing, Biostatistics, Mathematics +14