Results 71 to 80 of about 11,599 (161)

Rational Design of Field-Effect Sensors Using Partial Differential Equations, Bayesian Inversion, and Artificial Neural Networks. [PDF]

Sensors (Basel), 2022
Khodadadian A, Parvizi M, Teshnehlab M, Heitzinger C.   +3 more
europepmc   +1 more source

A Novel Bayesian Geophysical Inversion Method to Address Loss Function Bias: The Iterative Normalizing Flows Model

Journal of Geophysical Research: Machine Learning and Computation
Geophysical inversion plays a pivotal role in understanding the Earth's internal structure. Recently generative neural networks (GNNs), such as normalizing flows models (NFMs), have gained popularity for solving Bayesian inversion problems.
Binbin Liao, Xiaodong Chen, Jianqiao Xu, Jiangcun Zhou, Heping Sun   +4 more
doaj   +1 more source

Bayesian inverse analysis of unsaturated slope parameters using fine-tuned deep operator network model

Yantu gongcheng xuebao
Bayesian method infers the posterior distribution of slope parameters by combining prior distribution with filed time-series monitoring data. This process requires extensive computational resources due to repeated calls to time-consuming numerical models.
JIE Honghu 1, 2, JIANG Shuihua 1, 2, WAN Jianhong 1, 2, CHANG Zhilu 1, 2, HUANG Jinsong 1, ZHOU Chuangbing 1, 2
doaj   +1 more source

Two-dimensional Bayesian inversion of magnetotelluric data using trans-dimensional Gaussian processes. [PDF]

Geophys J Int, 2021
Blatter D, Ray A, Key K.
europepmc   +1 more source

A Full Bayesian Approach for Inverse Problems [PDF]

, 1996
Presented at MaxEnt95. Appeared in Maximum Entropy and Bayesian Methods, K. Hanson and R. Silver (Ed.), Kluwer Academic Publishers, pp: 135-144, (http://www.wkap.nl/prod/b/0-7923-4311-5)
openaire   +2 more sources

Surrogate-accelerated Bayesian Inversion for Exoplanet Interior Characterization

The Astrophysical Journal
Characterizing the interior structure of exoplanets is an inverse problem often solved using Bayesian inference, but this approach is hampered by the high computational cost of planetary structure models.
Tijn de Wringer, Caroline Dorn, Emily O. Garvin, Stefano Marelli   +3 more
doaj   +1 more source

Bottom Multi-Parameter Bayesian Inversion Based on an Acoustic Backscattering Model

Journal of Marine Science and Engineering
The geoacoustic and physical properties of the bottom, as well as spatial distribution, are crucial factors in analyzing the underwater acoustic field structure and establishing a geoacoustic model.
Yi Zheng, Shengqi Yu, Zhiliang Qin, Xueqin Liu, Chuang Xie, Mengting Liu, Jixiang Zhao   +6 more
doaj   +1 more source

Auto-Encoding Bayesian Inverse Games

CoRR
When multiple agents interact in a common environment, each agent's actions impact others' future decisions, and noncooperative dynamic games naturally capture this coupling. In interactive motion planning, however, agents typically do not have access to a complete model of the game, e.g., due to unknown objectives of other players.
Xinjie Liu, Lasse Peters, Javier Alonso-Mora, Ufuk Topcu, David Fridovich-Keil   +4 more
openaire   +2 more sources

Analysis and Computation for Bayesian Inverse Problems [PDF]

, 2016
Many inverse problems involve the estimation of a high dimensional quantity, such as a function, from noisy indirect measurements. These problems have received much study from both classical and statistical directions, with each approach having its own advantages and disadvantages.
openaire   +1 more source

High-resolution Bayesian Virtual Epileptic Patient using neural field models. [PDF]

Netw Neurosci
Vattikonda AN, Hashemi M, Woodman MM, Lemarechal JD, Daini D, Bartolomei F, Jirsa V.   +6 more
europepmc   +1 more source