Lianghao Cao

16 papers Journal 16
YearRankTypeTitle / Venue / Authors
2026 J jnl
LazyDINO: Fast, Scalable, and Efficiently Amortized Bayesian Inversion via Structure-Exploiting and Surrogate-Driven Measure Transport.
J. Mach. Learn. Res.
Lianghao Cao, Joshua Chen, Michael Brennan, Thomas O'Leary-Roseberry, Youssef Marzouk, Omar Ghattas
2026 J jnl
Optimal Experimental Design for Reliable Learning of History-Dependent Constitutive Laws.
CoRR
Kaushik Bhattacharya, Lianghao Cao, Andrew M. Stuart
2026 J jnl
Predictive Science: A Quest for the Holy.
Comput. Sci. Eng.
Abani K. Patra, Danial Faghihi, Prashant K. Jha, Lianghao Cao, Kathryn A. Farrell-Maupin
2025 J jnl
Derivative-Informed Fourier Neural Operator: Universal Approximation and Applications to PDE-Constrained Optimization.
CoRR
Boyuan Yao, Dingcheng Luo, Lianghao Cao, Nikola B. Kovachki, Thomas O'Leary-Roseberry, Omar Ghattas
2025 J jnl
Derivative-Informed Neural Operator Acceleration of Geometric MCMC for Infinite-Dimensional Bayesian Inverse Problems.
J. Mach. Learn. Res.
Lianghao Cao, Thomas O'Leary-Roseberry, Omar Ghattas
2025 J jnl
Learning Memory and Material Dependent Constitutive Laws.
CoRR
Kaushik Bhattacharya, Lianghao Cao, George Stepaniants, Andrew M. Stuart, Margaret Trautner
2024 J jnl
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport.
J. Comput. Phys.
Ricardo Baptista, Lianghao Cao, Joshua Chen, Omar Ghattas, Fengyi Li, Youssef M. Marzouk, J. Tinsley Oden
2024 J jnl
Efficient geometric Markov chain Monte Carlo for nonlinear Bayesian inversion enabled by derivative-informed neural operators.
CoRR
Lianghao Cao, Thomas O'Leary-Roseberry, Omar Ghattas
2024 J jnl
LazyDINO: Fast, scalable, and efficiently amortized Bayesian inversion via structure-exploiting and surrogate-driven measure transport.
CoRR
Lianghao Cao, Joshua Chen, Michael Brennan, Thomas O'Leary-Roseberry, Youssef M. Marzouk, Omar Ghattas
2023 J jnl
Bayesian model calibration for diblock copolymer thin film self-assembly using power spectrum of microscopy data.
CoRR
Lianghao Cao, Keyi Wu, J. Tinsley Oden, Peng Chen, Omar Ghattas
2023 J jnl
Optimal design of chemoepitaxial guideposts for the directed self-assembly of block copolymer systems using an inexact Newton algorithm.
J. Comput. Phys.
Dingcheng Luo, Lianghao Cao, Peng Chen, Omar Ghattas, J. Tinsley Oden
2023 J jnl
Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems.
J. Comput. Phys.
Lianghao Cao, Thomas O'Leary-Roseberry, Prashant K. Jha, J. Tinsley Oden, Omar Ghattas
2022 J jnl
A Globally Convergent Modified Newton Method for the Direct Minimization of the Ohta-Kawasaki Energy with Application to the Directed Self-Assembly of Diblock Copolymers.
SIAM J. Sci. Comput.
Lianghao Cao, Omar Ghattas, J. Tinsley Oden
2022 J jnl
Optimal design of chemoepitaxial guideposts for directed self-assembly of block copolymer systems using an inexact-Newton algorithm.
CoRR
Dingcheng Luo, Lianghao Cao, Peng Chen, Omar Ghattas, J. Tinsley Oden
2022 J jnl
Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems.
CoRR
Lianghao Cao, Thomas O'Leary-Roseberry, Prashant K. Jha, J. Tinsley Oden, Omar Ghattas
2020 J jnl
A globally convergent modified Newton method for the direct minimization of the Ohta-Kawasaki energy with application to the directed self-assembly of diblock copolymers.
CoRR
Lianghao Cao, Omar Ghattas, J. Tinsley Oden