Daniel Zhengyu Huang

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 18

Top Topics

Feature Dimension

Bayesian Inference

Posterior Distribution

Probability Measure

Top Venues

J. Comput. Phys.

J. Mach. Learn. Res.

J. Open Source Softw.

Publications

José A. Carrillo, Yifan Chen, Daniel Zhengyu Huang, Jiaoyang Huang, Dongyi Wei
Fisher-Rao Gradient Flow: Geodesic Convexity and Functional Inequalities. CoRR (2024)
Yifan Chen, Daniel Zhengyu Huang, Jiaoyang Huang, Sebastian Reich, Andrew M. Stuart
Efficient, Multimodal, and Derivative-Free Bayesian Inference With Fisher-Rao Gradient Flows. CoRR (2024)
Daniel Zhengyu Huang, Nicholas H. Nelsen, Margaret Trautner
An operator learning perspective on parameter-to-observable maps. CoRR (2024)
Daniel Zhengyu Huang, Jiaoyang Huang, Zhengjiang Lin
Convergence Analysis of Probability Flow ODE for Score-based Generative Models. CoRR (2024)
Yifan Chen, Daniel Zhengyu Huang, Jiaoyang Huang, Sebastian Reich, Andrew M. Stuart
Sampling via Gradient Flows in the Space of Probability Measures. CoRR (2023)
Ziyuan Liu, Yuhang Wu, Daniel Zhengyu Huang, Hong Zhang, Xu Qian, Songhe Song
SPFNO: Spectral operator learning for PDEs with Dirichlet and Neumann boundary conditions. CoRR (2023)
Yifan Chen, Daniel Zhengyu Huang, Jiaoyang Huang, Sebastian Reich, Andrew M. Stuart
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance. CoRR (2023)
Oliver R. A. Dunbar, Ignacio Lopez-Gomez, Alfredo Garbuno-Iñigo, Daniel Zhengyu Huang, Eviatar Bach, Jin-Long Wu
EnsembleKalmanProcesses.jl: Derivative-free ensemble-based model calibration. J. Open Source Softw. 7 (80) (2022)
Luning Sun, Daniel Zhengyu Huang, Hao Sun, Jian-Xun Wang
Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty. CoRR (2022)
Daniel Zhengyu Huang, Tapio Schneider, Andrew M. Stuart
Iterated Kalman methodology for inverse problems. J. Comput. Phys. 463 (2022)
Jiaoyang Huang, Daniel Zhengyu Huang, Qing Yang, Guang Cheng
Power Iteration for Tensor PCA. J. Mach. Learn. Res. 23 (2022)
Daniel Zhengyu Huang, Jiaoyang Huang, Sebastian Reich, Andrew M. Stuart
Efficient Derivative-free Bayesian Inference for Large-Scale Inverse Problems. CoRR (2022)
Maarten V. de Hoop, Daniel Zhengyu Huang, Elizabeth Qian, Andrew M. Stuart
The Cost-Accuracy Trade-Off In Operator Learning With Neural Networks. CoRR (2022)
Zongyi Li, Daniel Zhengyu Huang, Burigede Liu, Anima Anandkumar
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries. CoRR (2022)
Gérard Ben Arous, Daniel Zhengyu Huang, Jiaoyang Huang
Long Random Matrices and Tensor Unfolding. CoRR (2021)
Daniel Zhengyu Huang, Jiaoyang Huang
Improve Unscented Kalman Inversion With Low-Rank Approximation and Reduced-Order Model. CoRR (2021)
Shunxiang Cao, Daniel Zhengyu Huang
Bayesian Calibration for Large-Scale Fluid Structure Interaction Problems Under Embedded/Immersed Boundary Framework. CoRR (2021)
Daniel Zhengyu Huang, Jiaoyang Huang
Unscented Kalman Inversion: Efficient Gaussian Approximation to the Posterior Distribution. CoRR (2021)