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Lianghao Cao
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2020 – today
- 2024
- [j4]Ricardo Baptista, Lianghao Cao, Joshua Chen, Omar Ghattas, Fengyi Li, Youssef M. Marzouk, J. Tinsley Oden:
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport. J. Comput. Phys. 503: 112844 (2024) - [i5]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 abs/2403.08220 (2024) - 2023
- [j3]Dingcheng Luo, Lianghao Cao, Peng Chen, Omar Ghattas, J. Tinsley Oden:
Optimal design of chemoepitaxial guideposts for the directed self-assembly of block copolymer systems using an inexact Newton algorithm. J. Comput. Phys. 485: 112101 (2023) - [j2]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: 112104 (2023) - [i4]Lianghao Cao, Keyi Wu, J. Tinsley Oden, Peng Chen, Omar Ghattas:
Bayesian model calibration for diblock copolymer thin film self-assembly using power spectrum of microscopy data. CoRR abs/2306.05398 (2023) - 2022
- [j1]Lianghao Cao, Omar Ghattas, J. Tinsley Oden:
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. 44(1): 51- (2022) - [i3]Dingcheng Luo, Lianghao Cao, Peng Chen, Omar Ghattas, J. Tinsley Oden:
Optimal design of chemoepitaxial guideposts for directed self-assembly of block copolymer systems using an inexact-Newton algorithm. CoRR abs/2208.01193 (2022) - [i2]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 abs/2210.03008 (2022) - 2020
- [i1]Lianghao Cao, Omar Ghattas, J. Tinsley Oden:
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 abs/2010.15271 (2020)
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