English
Related papers

Related papers: A fast multi-fidelity method with uncertainty quan…

200 papers

Modal decomposition techniques are important tools for the analysis of unsteady flows and, in order to provide meaningful insights with respect to coherent structures and their characteristic frequencies, the modes must possess a robust…

Fluid Dynamics · Physics 2023-08-24 Lucas F. de Souza , Renato F. Miotto , William R. Wolf

Models with a large number of latent variables are often used to fully utilize the information in big or complex data. However, they can be difficult to estimate using standard approaches, and variational inference methods are a popular…

Methodology · Statistics 2021-04-20 Rubén Loaiza-Maya , Michael Stanley Smith , David J. Nott , Peter J. Danaher

Although the inverted vial test has been widely used as a qualitative method for estimating fluid viscosity, quantitative rheological characterization has remained limited due to its complex, uncontrolled flow - driven by gravity, surface…

We present a multi-fidelity method for uncertainty quantification of parameter estimates in complex systems, leveraging generative models trained to sample the target conditional distribution. In the Bayesian inference setting, traditional…

Machine Learning · Computer Science 2025-04-03 Caroline Tatsuoka , Minglei Yang , Dongbin Xiu , Guannan Zhang

In this paper, we propose a fast extrinsic calibration method for fusing multiple inertial measurement units (MIMU) to improve visual-inertial odometry (VIO) localization accuracy. Currently, data fusion algorithms for MIMU highly depend on…

Robotics · Computer Science 2024-10-15 Youwei Yu , Yanqing Liu , Fengjie Fu , Sihan He , Dongchen Zhu , Lei Wang , Xiaolin Zhang , Jiamao Li

This paper presents a comparison of two multi-fidelity methods for the forward uncertainty quantification of a naval engineering problem. Specifically, we consider the problem of quantifying the uncertainty of the hydrodynamic resistance of…

Numerical Analysis · Mathematics 2021-11-29 Chiara Piazzola , Lorenzo Tamellini , Riccardo Pellegrini , Riccardo Broglia , Andrea Serani , Matteo Diez

The construction of efficient methods for uncertainty quantification in kinetic equations represents a challenge due to the high dimensionality of the models: often the computational costs involved become prohibitive. On the other hand,…

Numerical Analysis · Mathematics 2021-12-03 Giacomo Dimarco , Liu Liu , Lorenzo Pareschi , Xueyu Zhu

This work proposes a mmWave radar's scene flow estimation framework supervised by data from a widespread visual-inertial (VI) sensor suite, allowing crowdsourced training data from smart vehicles. Current scene flow estimation methods for…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Kezhong Liu , Yiwen Zhou , Mozi Chen , Jianhua He , Jingao Xu , Zheng Yang , Chris Xiaoxuan Lu , Shengkai Zhang

Precision radial velocity (RV) measurements continue to be a key tool to detect and characterise extrasolar planets. While instrumental precision keeps improving, stellar activity remains a barrier to obtain reliable measurements below 1-2…

Emulating high-accuracy computationally expensive models is crucial for tasks requiring numerous model evaluations, such as uncertainty quantification and optimization. When lower-fidelity models are available, they can be used to improve…

Methodology · Statistics 2024-10-30 Katerina Giannoukou , Stefano Marelli , Bruno Sudret

The paper presents an experimental study of the temporal behaviour of a bistable vertical cavity surface emitting laser (VCSEL) under the effect of optical feedback coming from vibrating diffusely-reflecting surface. We demonstrate that a…

Optics · Physics 2018-11-14 V. N. Chizhevsky

This paper proposes FAST-LIVO2: a fast, direct LiDAR-inertial-visual odometry framework to achieve accurate and robust state estimation in SLAM tasks and provide great potential in real-time, onboard robotic applications. FAST-LIVO2 fuses…

Data-driven RANS modeling is emerging as a promising methodology to exploit the information provided by high-fidelity data. However, its widespread application is limited by challenges in generalization and robustness to inconsistencies…

For objects of "large" vibration size such as waves on the sea surface, the choice of measurement method can create different understandings of system behavior. In one case, laser vibrometry measurements of a vibrating bar in a controlled…

Instrumentation and Detectors · Physics 2021-02-23 Michael C. Kobold , Michael McKinley

In Vision-Language-Actionf(VLA) models, robustness to real-world perturbations is critical for deployment. Existing methods target simple visual disturbances, overlooking the broader multi-modal perturbations that arise in actions,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Jianing Guo , Zhenhong Wu , Chang Tu , Yiyao Ma , Xiangqi Kong , Zhiqian Liu , Jiaming Ji , Shuning Zhang , Yuanpei Chen , Kai Chen , Qi Dou , Yaodong Yang , Xianglong Liu , Huijie Zhao , Weifeng Lv , Simin Li

Mode shape information play the essential role in deciding the spatial pattern of vibratory response of a structure. The uncertainty quantification of mode shape, i.e., predicting mode shape variation when the structure is subjected to…

Data Analysis, Statistics and Probability · Physics 2020-02-24 Kai Zhou , Jiong Tang

In this manuscript, we extend the variational multiscale enrichment (VME) method to model the dynamic response of hyperelastic materials undergoing large deformations. This approach enables the simulation of wave propagation under…

Computational Engineering, Finance, and Science · Computer Science 2025-11-19 Abhishek Arora , Caglar Oskay

Optical fiber modal noise is a limiting factor for high precision spectroscopy signal-to-noise in the near-infrared and visible. Unabated, especially when using highly coherent light sources for wavelength calibration, modal noise can…

Instrumentation and Methods for Astrophysics · Physics 2018-02-21 Ryan R. Petersburg , Tyler M. McCracken , Dominic Eggerman , Colby A. Jurgenson , David Sawyer , Andrew E. Szymkowiak , Debra A. Fischer

The simulation of many complex phenomena in engineering and science requires solving expensive, high-dimensional systems of partial differential equations (PDEs). To circumvent this, reduced-order models (ROMs) have been developed to speed…

Machine Learning · Computer Science 2025-10-27 Paolo Conti , Jonas Kneifl , Andrea Manzoni , Attilio Frangi , Jörg Fehr , Steven L. Brunton , J. Nathan Kutz

The numerical simulation of interaction between free flow and porous media, governed by coupled Stokes/Navier--Stokes--Darcy flows, is critical for understanding fluid filtration and physiological transport, yet it is hindered by the high…

Numerical Analysis · Mathematics 2026-05-15 Mengjia Chen , Changxin Qiu , Zhiping Mao , Menghui Xu