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Showing 1 to 15 of 15 for “"Bayesian Probability"”.
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Conservatism in a Bayesian Probability Situation as a Function of the Sex of the Subject
… to examine whether the conservatism present in a Bayesian probability situation could be partially attributable to the sex of the subjects performing the task. The experimental design required that the subjects estimate the probabilities of occurrence of two independent events. They were then …
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A unified framework for resource-bounded autonomous agents interacting with unknown environments
… optimality equations. Learning includes: (a) Bayesian probability theory, the theory for reasoning under uncertainty that extends logic; and (b) Bayes-Optimal agents, the application of Bayesian probability theory to the design of optimal adaptive agents. Then, two major problems of the …
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Reaching Consensus with uncertainty on a network
… and data fusion communities by applying Bayesian probability theory to the agreement problem. Unique to this approach is the ability to converge to the centralized Bayesian parameter estimate of non-Gaussian distributed variables over arbitrary, strongly connected networks and without the …
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An NMR Spectroscopy and Density-Functional Theory Study of Organometallic Complexes and Heme Proteins With Carbonyl, Alkylisocyanide, Nitrosoarene and Olefin Ligands: Applications to Structure Determinations
… 0°,l° for the Ao-substate when using a Bayesian probability or Z-surface method for structure determination. Results for the A1-substate (including the 57Fe NMR chemical shift and Mossbauer quadrupole splitting) are also consistent with close to linear and untilted Fe-C-O geometries (tau …
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Extensions and Applications of Ensemble-of-trees Methods in Machine Learning
… more recent ensemble techniques such as Bayesian Additive Regression Trees (BART) and Dynamic Trees (DT) focus on an underlying Bayesian probability model to generate the fits. These new probability model-based approaches show much promise versus their algorithmic counterparts, but also …
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Development of an Aggregation Methodology for Risk Analysis in Aerospace Conceptual Vehicle Design
… involved in aerospace conceptual design. Bayesian probability augmented by uncertainty modeling and expert calibration was employed in the methodology construction. Appropriate questionnaire techniques were used to acquire expert opinion; the responses served as input distributions to the …
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Machine Learning Simulation of Pedestrians Exploring the Built Environment
… were applied, including Computer Vision, Bayesian Probability Programming, Density-Based Clustering, and Reinforcement and Imitation Learning. This data-driven method included human trajectory data and three-dimensional site data, collected through fieldwork in Machu Picchu, located in …
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Acoustic classification of zooplankton
… the Pairwise Score Classifier (PSC) and the Bayesian Probability Classifier (BPC); these classifiers assign observations to a class based on similarities in covariance, mean, and variance, while accounting for model ambiguity and validity. These feature based and model based inversion …
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Physics of ultrasonic wave propagation in bone and heart characterized using Bayesian parameter estimation
… in bone and in heart tissue through the use of Bayesian probability theory. Quantitative ultrasound is a noninvasive modality used for clinical detection, characterization, and evaluation of bone quality and cardiovascular disease. Approaches that extend the state of knowledge of the physics …
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Bayesian Adaptive Designs for Early Phase Clinical Trials
… a series of events. A transparent yet efficient Bayesian probability model is applied to calculate the event happening probabilities in the presence of delayed outcomes, which incorporates the informative pending patients' remaining follow-up time into consideration. The T-3+3 design only models …
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Bayesian modelling of nuclear fusion experiments
Bayesian probability theory as a general framework for scientific modelling and inference is introduced and applied to nuclear fusion experiments in order to provide consistent inference solutions given multiple heterogeneous data sets. Fusion plasmas are complex physical systems, in which charged …
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Game theoretic analysis and design for network security
… observations are conditionally dependent, the Bayesian probability of error can no longer be expressed as a function of the marginal probabilities. We then characterize this probability of error based on the set of joint probabilities of the sensor messages. We show that there exist optimal …
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Characterization of quantum states: advances in quantum tomography and tests of nonlocality
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-04-06 without embargo terms
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Deep-Learning Based Multiple-Model Bayesian Architecture for Spacecraft Fault Estimation
… systematically organized autoencoders within a Bayesian framework, enabling early detection and classification of various spacecraft faults such as reaction-wheel damage, sensor faults, and power system degradation.</p> <p>To assess the effectiveness of this architecture, a range of performance …
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Pathological and Biomedical Characteristics of Spinal Cord Injury Determined Using Diffusion Tensor Imaging
Traumatic spinal cord injury: SCI) is the most devastating injury that often causes the victim permanent paralysis and undergo a lifetime of therapy and care. It is caused by a mechanical impact that ultimately causes pathophysiological consequences which at this moment in time are an unresolved …