Thomas O'Leary-Roseberry

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 13

Top Topics

Experimental Design

Inverse Problems

Constrained Optimization

Top Venues

J. Comput. Phys.

J. Sci. Comput.

Publications

Lianghao Cao, Thomas O'Leary-Roseberry, Omar Ghattas
Efficient geometric Markov chain Monte Carlo for nonlinear Bayesian inversion enabled by derivative-informed neural operators. CoRR (2024)
Umberto Villa, Thomas O'Leary-Roseberry
A note on the relationship between PDE-based precision operators and Matérn covariances. CoRR (2024)
Thomas O'Leary-Roseberry, Peng Chen, Umberto Villa, Omar Ghattas
Derivative-Informed Neural Operator: An efficient framework for high-dimensional parametric derivative learning. J. Comput. Phys. 496 (2024)
Keyi Wu, Thomas O'Leary-Roseberry, Peng Chen, Omar Ghattas
Large-Scale Bayesian Optimal Experimental Design with Derivative-Informed Projected Neural Network. J. Sci. Comput. 95 (1) (2023)
Lianghao Cao, Thomas O'Leary-Roseberry, Prashant K. Jha, J. Tinsley Oden, Omar Ghattas
Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems. J. Comput. Phys. 486 (2023)
Dingcheng Luo, Thomas O'Leary-Roseberry, Peng Chen, Omar Ghattas
Efficient PDE-Constrained optimization under high-dimensional uncertainty using derivative-informed neural operators. CoRR (2023)
Lianghao Cao, Thomas O'Leary-Roseberry, Prashant K. Jha, J. Tinsley Oden, Omar Ghattas
Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems. CoRR (2022)
Thomas O'Leary-Roseberry, Peng Chen, Umberto Villa, Omar Ghattas
Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning. CoRR (2022)
Keyi Wu, Thomas O'Leary-Roseberry, Peng Chen, Omar Ghattas
Derivative-informed projected neural network for large-scale Bayesian optimal experimental design. CoRR (2022)
Thomas O'Leary-Roseberry, Xiaosong Du, Anirban Chaudhuri, Joaquim R. R. A. Martins, Karen Willcox, Omar Ghattas
Adaptive Projected Residual Networks for Learning Parametric Maps from Sparse Data. CoRR (2021)
Thomas O'Leary-Roseberry, Omar Ghattas
Ill-Posedness and Optimization Geometry for Nonlinear Neural Network Training. CoRR (2020)
Thomas O'Leary-Roseberry, Umberto Villa, Peng Chen, Omar Ghattas
Derivative-Informed Projected Neural Networks for High-Dimensional Parametric Maps Governed by PDEs. CoRR (2020)
Thomas O'Leary-Roseberry, Nick Alger, Omar Ghattas
Low Rank Saddle Free Newton: Algorithm and Analysis. CoRR (2020)