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Lianghao Cao
Lianghao Cao
Postdoctoral Scholar Research Associate, California Institute of Technology
Adresă de e-mail confirmată pe caltech.edu - Pagina de pornire
Titlu
Citat de
Citat de
Anul
Bayesian-based predictions of COVID-19 evolution in Texas using multispecies mixture-theoretic continuum models
PK Jha, L Cao, JT Oden
Computational mechanics 66 (5), 1055-1068, 2020
512020
Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems
L Cao, T O'Leary-Roseberry, PK Jha, JT Oden, O Ghattas
Journal of Computational Physics 486, 112104, 2023
272023
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport
R Baptista, L Cao, J Chen, O Ghattas, F Li, YM Marzouk, JT Oden
Journal of Computational Physics 503, 112844, 2024
152024
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
L Cao, O Ghattas, JT Oden
SIAM Journal on Scientific Computing 44 (1), B51-B79, 2022
92022
Derivative-informed neural operator acceleration of geometric MCMC for infinite-dimensional Bayesian inverse problems
L Cao, T O'Leary-Roseberry, O Ghattas
arXiv preprint arXiv:2403.08220, 2024
6*2024
Predictive modeling and uncertainty quantification for diblock copolymer self-assembly
L Cao
52022
A nonlocal theory of heat transfer and micro-phase separation of nanostructured copolymers
PK Singh, L Cao, J Tan, D Faghihi
International Journal of Heat and Mass Transfer 215, 124474, 2023
42023
Optimal design of chemoepitaxial guideposts for the directed self-assembly of block copolymer systems using an inexact Newton algorithm
D Luo, L Cao, P Chen, O Ghattas, JT Oden
Journal of Computational Physics 485, 112101, 2023
42023
Bayesian model calibration for diblock copolymer thin film self-assembly using power spectrum of microscopy data and machine learning surrogate
L Cao, K Wu, JT Oden, P Chen, O Ghattas
Computer Methods in Applied Mechanics and Engineering, 116349, 2023
3*2023
LazyDINO: Fast, scalable, and efficiently amortized Bayesian inversion via structure-exploiting and surrogate-driven measure transport
L Cao, J Chen, M Brennan, T O'Leary-Roseberry, Y Marzouk, O Ghattas
arXiv preprint arXiv:2411.12726, 2024
12024
Learning Memory and Material Dependent Constitutive Laws
K Bhattacharya, L Cao, G Stepaniants, A Stuart, M Trautner
arXiv preprint arXiv:2502.05463, 2025
2025
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