Results 251 to 260 of about 15,893 (296)

Order-Restricted Inference for Exponentiated Rayleigh Distribution Under Multiple Step-Stress Accelerated Life Test. [PDF]

Entropy (Basel)
Yu B, Gui W.
europepmc   +1 more source

Deciphering stress perturbations throughout the 2025 M_w 7.1 Dingri, Southern Xizang Earthquake. [PDF]

Nat Commun
Ma Z, Li C, Zeng H, Chen H, Lyu M, Zhang Y, Dal Zilio L, Shan X, Wei S.   +8 more
europepmc   +1 more source

Enhanced Localization and Orientation Estimations in Focal EEG Source Imaging Using SVD-Based Coordinate Transform. [PDF]

Brain Topogr
Lahtinen J, Koulouri A.
europepmc   +1 more source

Integrating physics and machine learning for unified seismic forward modeling and reservoir property inversion. [PDF]

Sci Rep
Zayier Y, Yalikun Y, Cheng Y, Yang D.
europepmc   +1 more source

Bayesian Dix inversion

Geophysics, 2011
Abstract We have developed a Bayesian method for Dix inversion and illustrated it with examples from the North Sea. The method is a constrained Dix inversion in which the uncertainty of the estimated interval velocities is an integral part of the solution.
Arild Buland, Odd Kolbjørnsen, Andrew J. Carter   +2 more
openaire   +2 more sources

Neuro-Bayesian facies inversion of prestack seismic data from a carbonate reservoir in Iran

Journal of Petroleum Science and Engineering, 2015
Facies study is a powerful tool to better understand complexities of carbonate reservoirs. Porosity, frame flexibility factor and bulk modulus of fluid are believed to be the most proper rock physical parameters to define desired facies in carbonate ...
Sadegh Karimpouli, Alireza Malehmir
exaly   +2 more sources

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Inverse Halftoning Based on the Bayesian Theorem

IEEE Transactions on Image Processing, 2011
This study proposes a method which can generate high quality inverse halftone images from halftone images. This method can be employed prior to any signal processing over a halftone image or the inverse halftoning used in JBIG2. The proposed method utilizes the least-mean-square (LMS) algorithm to establish a relationship between the current processing
Yun-Fu Liu, Jing-Ming Guo, Jiann-Der Lee
openaire   +3 more sources

Hierarchical Bayesian Inverse Reinforcement Learning

IEEE Transactions on Cybernetics, 2015
Inverse reinforcement learning (IRL) is the problem of inferring the underlying reward function from the expert's behavior data. The difficulty in IRL mainly arises in choosing the best reward function since there are typically an infinite number of reward functions that yield the given behavior data as optimal.
Choi, JD Choi, Jae-Deug, Kim, KE Kim, Kee-Eung   +1 more
openaire   +3 more sources

Bayesian Inverse Problems

2021
Many problems in science and engineering consist of estimating some unknown parameters of a physical system from limited and noisy observations. In practical conditions, these problems are often unstable; hence, they should be treated in an appropriate framework in the theory of inverse problems.
Juan Chiachío-Ruano, Manuel Chiachío-Ruano, Shankar Sankararaman   +2 more
openaire   +2 more sources

Bayesian Estimation of Inverse Dose Response

Biometrics, 2008
Summary Inverse dose–response estimation refers to the inference of an effective dose of some agent that gives a desired probability of response, say 0.5. We consider inverse dose response for two agents, an application that has not received much attention in the literature.
Hu, Bo, Ji, Yuan, Tsui, Kam-Wah
openaire   +3 more sources