Results 31 to 40 of about 964,661 (301)
Bayesian Linear Regression [PDF]
, 2009 The paper is concerned with Bayesian analysis under prior-data conflict, i.e. the situation when observed data are rather unexpected under the prior (and the sample size is not large enough to eliminate the influence of the prior).
Walter, Gero, Augustin, Thomas
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Fixed Point Results in Orthogonal Neutrosophic Metric Spaces
Complexity, 2021 Neutrosophy deals with neutrosophic logic, probability, and sets. Actually, the neutrosophic set is a generalization of the classical set, fuzzy set, and intuitionistic fuzzy set.
Umar Ishtiaq +5 more
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IEEE Access, 2022 Dynamic target threat assessment can be regarded as a classical multiple attribute group decision-making (MAGDM) issue. Triangular fuzzy numbers (TFNs) can fully describe imprecise and fuzzy information for target threat assessment. Thus, to consider the
Ruojing Zhao, Fengbao Yang, Linna Ji
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Bayesian Hybrid Automata: A Formal Model of Justified Belief in Interacting Hybrid Systems Subject to Imprecise Observation [PDF]
Leibniz Transactions on Embedded Systems, 2022 Hybrid discrete-continuous system dynamics arises when discrete actions, e.g. by a decision algorithm, meet continuous behaviour, e.g. due to physical processes and continuous control.
Kröger, Paul, Fränzle, Martin
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Quantum Mechanics and Imprecise Probability [PDF]
Journal of Statistical Physics, 2008 An extension of the Born rule, the {\it quantum typicality rule}, has recently been proposed [B. Galvan: Found. Phys. 37, 1540-1562 (2007)]. Roughly speaking, this rule states that if the wave function of a particle is split into non-overlapping wave packets, the particle stays approximately inside the support of one of the wave packets, without ...
openaire +3 more sources
Depth-Aware Object Tracking With a Conditional Variational Autoencoder
IEEE Access, 2021 Object tracking is a fundamental task in computer vision and artificial intelligence. However, state-of-the-art object tracking approaches are still prone to failures and are imprecise when applied to challenging scenarios, and their results are ...
Wenhui Huang, Jason Gu, Yinchen Guo
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On Sharp Identification Regions for Regression Under Interval Data [PDF]
, 2013 The reliable analysis of interval data (coarsened data) is one of the most promising applications of imprecise probabilities in statistics. If one refrains from making untestable, and often materially unjustified, strong assumptions on the coarsening ...
Schollmeyer, Georg, Augustin, Thomas
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The Failure-tree Analysis Based on Imprecise Probability and its Application on Tunnel Project
Chemical Engineering Transactions, 2017 Due to the inherent uncertainties in ground and groundwater conditions, tunnel projects often have to face potential risks of cost overrun or schedule delay.
Lei Huang
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Fuzzy Portfolio Selection in COVID-19 Spreading Period Using Fuzzy Goal Programming Model
Mathematics, 2021 While the international lockdown for the COVID-19 pandemic has greatly influenced the global economy, we are still confronted with the dilemma about the economy recession when the stock market hits record highs repeatedly.
Ruey-Chyn Tsaur +2 more
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Bayesian Learning for a Class of Priors with Prescribed Marginals [PDF]
, 2006 We present Bayesian updating of an imprecise probability measure, represented by a class of precise multidimensional probability measures. Choice and analysis of our class are motivated by expert interviews that we conducted with modelers in the context ...
Augustin, Thomas +2 more
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