Daniel Zhengyu Huang (黄政宇)

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Charbel FarhatVivian Church Hoff Professor in the School of Engineering, Stanford UniversityPatvirtintas el. paštas stanford.edu
Philip AveryResearch Engineer, Stanford UniversityPatvirtintas el. paštas stanford.edu
Jason RabinovitchAssistant Professor, Stevens Institute of TechnologyPatvirtintas el. paštas stevens.edu
Andrew M StuartComputing + Mathematical Sciences, CaltechPatvirtintas el. paštas caltech.edu
Armen DerkevorkianJet Propulsion Laboratory, California Institute of TechnologyPatvirtintas el. paštas jpl.nasa.gov
Jiaoyang HuangUniversity of PennsylvaniaPatvirtintas el. paštas wharton.upenn.edu
Eric DarveStanfordPatvirtintas el. paštas stanford.edu
Kailai XuStanford UniversityPatvirtintas el. paštas stanford.edu
Raunak BorkerSenior R&D Engineer, Discovery, AnsysPatvirtintas el. paštas ansys.com
Sebastian GrimbergAWS Center for Quantum ComputingPatvirtintas el. paštas amazon.com
Zongyi LiCaltechPatvirtintas el. paštas caltech.edu
Anima AnandkumarCalifornia Institute of Technology and NVIDIAPatvirtintas el. paštas caltech.edu
Tapio SchneiderProfessor, California Institute of TechnologyPatvirtintas el. paštas caltech.edu
Sebastian ReichUniversity of PotsdamPatvirtintas el. paštas uni-potsdam.de
Per-Olof PerssonUniversity of California, BerkeleyPatvirtintas el. paštas berkeley.edu
Matthew ZahrAssistant ProfessorPatvirtintas el. paštas nd.edu
Burigede LiuGranta Design Assistant Professor, University of CambridgePatvirtintas el. paštas cam.ac.uk
Yifan ChenCourant Institute, NYUPatvirtintas el. paštas nyu.edu
Elizabeth QianGeorgia Institute of TechnologyPatvirtintas el. paštas gatech.edu
Maarten de HoopRice UniversityPatvirtintas el. paštas rice.edu

Stebėti

Daniel Zhengyu Huang (黄政宇)

Peking University / Caltech / Stanford

Patvirtintas el. paštas bicmr.pku.edu.cn - Pagrindinis puslapis

Computational Mathematics Fluid Structure Interaction Bayesian Inverse Problems Machine Learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
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	182*	2020
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	181	2023
Learning constitutive relations using symmetric positive definite neural networks K Xu, DZ Huang, E Darve Journal of Computational Physics 428, 110072, 2021	149	2021
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	75	2022
Iterated Kalman methodology for inverse problems DZ Huang, T Schneider, AM Stuart Journal of Computational Physics 463, 111262, 2022	59*	2022
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	58*	2019
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	50	2020
Efficient derivative-free Bayesian inference for large-scale inverse problems DZ Huang, J Huang, S Reich, AM Stuart Inverse Problems 38 (12), 125006, 2022	42*	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	42*	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	40	2018
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	27	2021
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	27	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	24	2019
Power iteration for tensor PCA J Huang, DZ Huang, Q Yang, G Cheng Journal of Machine Learning Research 23 (128), 1-47, 2022	22	2022
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	19	2020
Long random matrices and tensor unfolding G Ben Arous, DZ Huang, J Huang* The Annals of Applied Probability 33 (6B), 5753-5780, 2023	16	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	15	2019
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	13	2023
An operator learning perspective on parameter-to-observable maps DZ Huang, NH Nelsen, M Trautner* Foundations of Data Science, 2024	10	2024
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	10*	2021

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