A family of position- and orientation-independent embedded boundary methods for viscous flow and fluid-structure interaction problems. - Daniel Zhengyu Huang; Dante De Santis; Charbel Farhat (J. Comput. Phys., 2018)

An Embedded Boundary Approach for Resolving the Contribution of Cable Subsystems to Fully Coupled Fluid-Structure Interaction. - Daniel Zhengyu Huang; Philip Avery; Charbel Farhat (CoRR, 2019)

Modeling, simulation and validation of supersonic parachute inflation dynamics during Mars landing. - Daniel Zhengyu Huang; Philip Avery; Charbel Farhat; Jason Rabinovitch; Armen Derkevorkian; Lee D. Peterson (CoRR, 2019)

A computationally tractable framework for nonlinear dynamic multiscale modeling of membrane fabric. - Philip Avery; Daniel Zhengyu Huang; Wanli He; Johanna Ehlers; Armen Derkevorkian; Charbel Farhat (CoRR, 2020)

High-order partitioned spectral deferred correction solvers for multiphysics problems. - Daniel Zhengyu Huang; Will Pazner; Per-Olof Persson; Matthew J. Zahr (J. Comput. Phys., 2020)

Learning constitutive relations from indirect observations using deep neural networks. - Daniel Zhengyu Huang; Kailai Xu; Charbel Farhat; Eric Darve (J. Comput. Phys., 2020)

Unscented Kalman Inversion. - Daniel Zhengyu Huang; Tapio Schneider; Andrew M. Stuart (CoRR, 2021)

Improve Unscented Kalman Inversion With Low-Rank Approximation and Reduced-Order Model. - Daniel Zhengyu Huang; Jiaoyang Huang (CoRR, 2021)

Unscented Kalman Inversion: Efficient Gaussian Approximation to the Posterior Distribution. - Daniel Zhengyu Huang; Jiaoyang Huang (CoRR, 2021)

Bayesian Calibration for Large-Scale Fluid Structure Interaction Problems Under Embedded/Immersed Boundary Framework. - Shunxiang Cao; Daniel Zhengyu Huang (CoRR, 2021)

Long Random Matrices and Tensor Unfolding. - Gérard Ben Arous; Daniel Zhengyu Huang; Jiaoyang Huang (CoRR, 2021)

Learning constitutive relations using symmetric positive definite neural networks. - Kailai Xu; Daniel Zhengyu Huang; Eric Darve (J. Comput. Phys., 2021)

Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty. - Luning Sun; Daniel Huang 005; Hao Sun 002; Jian-Xun Wang 001 (NeurIPS, 2022)

The Cost-Accuracy Trade-Off In Operator Learning With Neural Networks. - Maarten V. de Hoop; Daniel Zhengyu Huang; Elizabeth Qian; Andrew M. Stuart (CoRR, 2022)

Efficient Derivative-free Bayesian Inference for Large-Scale Inverse Problems. - Daniel Zhengyu Huang; Jiaoyang Huang; Sebastian Reich; Andrew M. Stuart (CoRR, 2022)

Iterated Kalman methodology for inverse problems. - Daniel Zhengyu Huang; Tapio Schneider; Andrew M. Stuart (J. Comput. Phys., 2022)

Power Iteration for Tensor PCA. - Jiaoyang Huang; Daniel Zhengyu Huang; Qing Yang; Guang Cheng (J. Mach. Learn. Res., 2022)

EnsembleKalmanProcesses.jl: Derivative-free ensemble-based model calibration. - Oliver R. A. Dunbar; Ignacio Lopez-Gomez; Alfredo Garbuno-Iñigo; Daniel Zhengyu Huang; Eviatar Bach; Jinlong Wu (J. Open Source Softw., 2022)

Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance. - Yifan Chen; Daniel Zhengyu Huang; Jiaoyang Huang; Sebastian Reich; Andrew M. Stuart (CoRR, 2023)

Sampling via Gradient Flows in the Space of Probability Measures. - Yifan Chen; Daniel Zhengyu Huang; Jiaoyang Huang; Sebastian Reich; Andrew M. Stuart (CoRR, 2023)

SPFNO: Spectral operator learning for PDEs with Dirichlet and Neumann boundary conditions. - Ziyuan Liu; Yuhang Wu; Daniel Zhengyu Huang; Hong Zhang; Xu Qian; Songhe Song (CoRR, 2023)

Fourier Neural Operator with Learned Deformations for PDEs on General Geometries. - Zongyi Li; Daniel Zhengyu Huang; Burigede Liu; Anima Anandkumar (J. Mach. Learn. Res., 2023)

An operator learning perspective on parameter-to-observable maps. - Daniel Zhengyu Huang; Nicholas H. Nelsen; Margaret Trautner (CoRR, 2024)

Efficient, Multimodal, and Derivative-Free Bayesian Inference With Fisher-Rao Gradient Flows. - Yifan Chen; Daniel Zhengyu Huang; Jiaoyang Huang; Sebastian Reich; Andrew M. Stuart (CoRR, 2024)

Fisher-Rao Gradient Flow: Geodesic Convexity and Functional Inequalities. - José A. Carrillo 001; Yifan Chen; Daniel Zhengyu Huang; Jiaoyang Huang; Dongyi Wei (CoRR, 2024)

Stable Derivative Free Gaussian Mixture Variational Inference for Bayesian Inverse Problems. - Baojun Che; Yifan Chen; Zhenghao Huan; Daniel Zhengyu Huang; Weijie Wang (CoRR, 2025)

Point Cloud Neural Operator for Parametric PDEs on Complex and Variable Geometries. - Chenyu Zeng; Yanshu Zhang; Jiayi Zhou; Yuhan Wang; Zilin Wang; Yuhao Liu; Lei Wu; Daniel Zhengyu Huang (CoRR, 2025)

Fast Convergence for High-Order ODE Solvers in Diffusion Probabilistic Models. - Daniel Zhengyu Huang; Jiaoyang Huang; Zhengjiang Lin (CoRR, 2025)

Convergence Analysis of Probability Flow ODE for Score-Based Generative Models. - Daniel Zhengyu Huang; Jiaoyang Huang; Zhengjiang Lin (IEEE Trans. Inf. Theory, 2025)