Results 241 to 250 of about 70,196 (284)
Ground motion inversion method based on generalized chaotic particle swarm optimization. [PDF]
PLoS OneSun B, Qi L.
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Seismic evidence of liquid water at the base of Mars' upper crust. [PDF]
Natl Sci RevSun W, Tkalčić H, Malusà MG, Pan Y.
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Virtual Brain Inference (VBI), a flexible and integrative toolkit for efficient probabilistic inference on whole-brain models. [PDF]
ElifeZiaeemehr A +5 more
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The Leading Edge, 2008
Many times we are faced with the business decision of whether or not to develop a sand that is at the limit of seismic resolution and near the noise level of the data. The critical issue is developing a reasonable certainty that there is enough volume of hydrocarbons to develop. A popular approach is to use Bayesian methods to determine the probability
Michael E. Glinsky +7 more
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Many times we are faced with the business decision of whether or not to develop a sand that is at the limit of seismic resolution and near the noise level of the data. The critical issue is developing a reasonable certainty that there is enough volume of hydrocarbons to develop. A popular approach is to use Bayesian methods to determine the probability
Michael E. Glinsky +7 more
openaire +2 more sources
Bayesian geoacoustic inversion.
The Journal of the Acoustical Society of America, 2010This paper describes a general Bayesian approach to estimating seabed geoacoustic parameters from ocean acoustic data, which is also applicable to other inverse problems. Within a Bayesian formulation, the complete solution is given by the posterior probability density (PPD), which includes both data and prior information.
Stan E. Dosso, Jan Dettmer
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GEOPHYSICS, 2011
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. The method combines available geologic prior knowledge with the information in the picked rms velocities ...
Arild Buland +2 more
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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. The method combines available geologic prior knowledge with the information in the picked rms velocities ...
Arild Buland +2 more
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Hierarchical Bayesian Inverse Reinforcement Learning
IEEE Transactions on Cybernetics, 2015Inverse 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 +1 more
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Bayesian Estimation of Inverse Dose Response
Biometrics, 2008Summary 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
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