Daniel Zhengyu Huang (黄政宇)
Daniel Zhengyu Huang (黄政宇)
Peking University / Caltech / Stanford
Verified email at - Homepage
Cited by
Cited by
Learning constitutive relations from indirect observations using deep neural networks
DZ Huang*, K Xu*, C Farhat, E Darve
Journal of Computational Physics 416, 109491, 2020
Learning constitutive relations using symmetric positive definite neural networks
K Xu*, DZ Huang*, E Darve
Journal of Computational Physics 428, 110072, 2021
Fourier neural operator with learned deformations for pdes on general geometries
Z Li, DZ Huang, B Liu, A Anandkumar
Journal of Machine Learning Research 24 (388), 1-26, 2023
Mesh adaptation framework for embedded boundary methods for computational fluid dynamics and fluid‐structure interaction
R Borker, D Huang, S Grimberg, C Farhat, P Avery, J Rabinovitch
International Journal for Numerical Methods in Fluids 90 (8), 389-424, 2019
The cost-accuracy trade-off in operator learning with neural networks
M De Hoop*, DZ Huang*, E Qian*, AM Stuart*
Journal of Machine Learning 1, 299-341, 2022
Modeling, simulation and validation of supersonic parachute inflation dynamics during Mars landing
DZ Huang, P Avery, C Farhat, J Rabinovitch, A Derkevorkian, ...
AIAA scitech 2020 forum, 0313, 2020
Iterated Kalman methodology for inverse problems
DZ Huang, T Schneider, AM Stuart
Journal of Computational Physics 463, 111262, 2022
A family of position-and orientation-independent embedded boundary methods for viscous flow and fluid–structure interaction problems
DZ Huang, D De Santis, C Farhat
Journal of Computational Physics 365, 74-104, 2018
Simulation of parachute inflation dynamics using an Eulerian computational framework for fluid-structure interfaces evolving in high-speed turbulent flows
Z Huang, P Avery, C Farhat, J Rabinovitch, A Derkevorkian, LD Peterson
2018 AIAA Aerospace Sciences Meeting, 1540, 2018
Efficient derivative-free Bayesian inference for large-scale inverse problems
DZ Huang, J Huang, S Reich, AM Stuart
Inverse Problems 38 (12), 125006, 2022
A computationally tractable framework for nonlinear dynamic multiscale modeling of membrane woven fabrics
P Avery, DZ Huang, W He, J Ehlers, A Derkevorkian, C Farhat
International Journal for Numerical Methods in Engineering 122 (10), 2598-2625, 2021
An embedded boundary approach for resolving the contribution of cable subsystems to fully coupled fluid‐structure interaction
DZ Huang, P Avery, C Farhat
International Journal for Numerical Methods in Engineering 122 (19), 5409-5429, 2021
High-order, linearly stable, partitioned solvers for general multiphysics problems based on implicit–explicit Runge–Kutta schemes
DZ Huang, PO Persson, MJ Zahr
Computer Methods in Applied Mechanics and Engineering 346, 674-706, 2019
High-order partitioned spectral deferred correction solvers for multiphysics problems
DZ Huang, W Pazner, PO Persson, MJ Zahr
Journal of Computational Physics 412, 109441, 2020
Power iteration for tensor pca
J Huang, DZ Huang, Q Yang, G Cheng
Journal of Machine Learning Research 23 (128), 1-47, 2022
Long random matrices and tensor unfolding
G Ben Arous*, DZ Huang*, J Huang*
The Annals of Applied Probability 33 (6B), 5753-5780, 2023
Towards a validated fsi computational framework for supersonic parachute deployments
J Rabinovitch, DZ Huang, R Borker, P Avery, C Farhat, A Derkevorkian, ...
AIAA Aviation 2019 Forum, 3275, 2019
Homogenized flux-body force treatment of compressible viscous porous wall boundary conditions
DZ Huang, ML Wong, SK Lele, C Farhat
AIAA Journal 59 (6), 2045-2059, 2021
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance
Y Chen*, DZ Huang*, J Huang*, S Reich*, AM Stuart*
arXiv preprint arXiv:2302.11024, 2023
Effects of structural parameters on the FSI simulation of supersonic parachute deployments
A Derkevorkian, P Avery, C Farhat, J Rabinovitch, L Peterson
AIAA Aviation 2019 Forum, 3276, 2019
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