@Article{AAM-40-1,
author = {Zhang, Lei and Zhang, Pingwen and Zheng, Xiangcheng},
title = {Probabilistic Error Estimate for Numerical Discretization of High-Index Saddle Dynamics with Inaccurate Models},
journal = {Annals of Applied Mathematics},
year = {2024},
volume = {40},
number = {1},
pages = {1--20},
abstract = {<p style="text-align: justify;">We prove probabilistic error estimates for high-index saddle dynamics with or without constraints to account for the inaccurate values of the model,
which could be encountered in various scenarios such as model uncertainties or
surrogate model algorithms via machine learning methods. The main contribution lies in incorporating the probabilistic error bound of the model values with
the conventional error estimate methods for high-index saddle dynamics. The
derived results generalize the error analysis of deterministic saddle dynamics
and characterize the affect of the inaccuracy of the model on the convergence
rate.</p>},
issn = {},
doi = {https://doi.org/10.4208/aam.OA-2023-0030},
url = {https://global-sci.com/article/90853/probabilistic-error-estimate-for-numerical-discretization-of-high-index-saddle-dynamics-with-inaccurate-models}
}