Παρακολούθηση
Han Gao (高涵)
Han Gao (高涵)
Harvard University
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα seas.harvard.edu - Αρχική σελίδα
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data
L Sun, H Gao, S Pan, JX Wang
Computer Methods in Applied Mechanics and Engineering 361, 112732, 2020
8402020
PhyGeoNet: Physics-informed geometry-adaptive convolutional neural networks for solving parameterized steady-state PDEs on irregular domain
H Gao, L Sun, JX Wang
Journal of Computational Physics 428, 110079, 2021
5152021
Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems
H Gao, MJ Zahr, JX Wang
Computer Methods in Applied Mechanics and Engineering 390, 114502, 2022
2092022
Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels
H Gao, L Sun, JX Wang
Physics of Fluids 33 (7), 2021
1982021
Predicting physics in mesh-reduced space with temporal attention
X Han, H Gao, T Pfaff, JX Wang, LP Liu
ICLR 2022, 2022
972022
SSR-VFD: Spatial super-resolution for vector field data analysis and visualization
L Guo, S Ye, J Han, H Zheng, H Gao, DZ Chen, JX Wang, C Wang
Proceedings of IEEE Pacific visualization symposium, 2020
632020
Non-intrusive model reduction of large-scale, nonlinear dynamical systems using deep learning
H Gao, JX Wang, MJ Zahr
Physica D: Nonlinear Phenomena 412, 132614, 2020
542020
A bi-fidelity surrogate modeling approach for uncertainty propagation in three-dimensional hemodynamic simulations
H Gao, X Zhu, JX Wang
Computer Methods in Applied Mechanics and Engineering 366, 113047, 2020
242020
A bi-fidelity ensemble Kalman method for PDE-constrained inverse problems in computational mechanics
H Gao, JX Wang
Computational Mechanics 67 (4), 1115-1131, 2021
192021
Bayesian conditional diffusion models for versatile spatiotemporal turbulence generation
H Gao, X Han, X Fan, L Sun, LP Liu, L Duan, JX Wang
Computer Methods in Applied Mechanics and Engineering, 2023
112023
Unifying predictions of deterministic and stochastic physics in mesh-reduced space with sequential flow generative model
L Sun, X Han, H Gao, JX Wang, L Liu
Advances in Neural Information Processing Systems 36, 2024
92024
Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution
R Wang, H Gao, R Walters, TE Smidt
The Forty-first International Conference on Machine Learning, 2023
9*2023
Patchgt: Transformer over non-trainable clusters for learning graph representations
H Gao, X Han, J Huang, JX Wang, L Liu
Learning on Graphs Conference, 27: 1-27: 25, 2022
62022
Generative learning for forecasting the dynamics of high-dimensional complex systems
H Gao, S Kaltenbach, P Koumoutsakos
Nature Communications 15 (1), 8904, 2024
4*2024
Generative learning of the solution of parametric partial differential equations using guided diffusion models and virtual observations
H Gao, S Kaltenbach, P Koumoutsakos
arXiv preprint arXiv:2408.00157, 2024
32024
Numerical simulation of the cavitation flow around a hydrofoil based on a coupled CFD-PBM model
Q Liu, K Xu, H Gao, RK Agarwal
AIAA Scitech 2019 Forum, 2305, 2019
32019
Numerical study of a hovering helicopter rotor blade in ground effect
H Gao, RK Agarwal
AIAA Scitech 2019 Forum, 1099, 2019
32019
Numerical Investigation of a Submerged Water Jet Impinging at Various Angles on Ground
X Zhang, RK Agarwal, H Gao, L Zhou
AIAA Scitech 2020 Forum, 2038, 2020
12020
Study of Round Jet Impingement in Proximity of Ground and Water Surface
H Gao, Q Liu, Q Qu, RK Agarwal
Journal of Aircraft 56 (6), 2236-2247, 2019
12019
Numerical investigation of cavitation characteristics of a liquid oxygen turbo pump
Q Liu, L Gong, H Gao, RK Agarwal
2018 Fluid Dynamics Conference, 3222, 2018
12018
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