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CBCT-Based synthetic CT image generation using conditional denoising diffusion probabilistic model. [PDF]

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Constructing probabilistic models

International Journal of Medical Informatics, 1997
Bayesian networks have become one of the most popular probabilistic techniques in AI, largely due to the development of several efficient inference algorithms. In this paper we describe a heuristic method for constructing Bayesian networks. Our construction method relies on the relationship between Bayesian networks and decomposable models, a special ...
R, Jirousek, N, Kushmerick
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Probabilistic opponent-model search

Information Sciences, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Donkers, H.H.L.M.   +2 more
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Probabilistic Modelling

Journal of the American Statistical Association, 1999
Jem N. Corcoran, Isi Mitrani
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Probabilistic Modelling

1997
Probabilistic modelling is the most cost-effective means of performance and reliability evaluation of complex dynamic systems. This self-contained text will be welcomed by students and teachers for its no-nonsense treatment of the basic results and examples of their application. The only mathematical background that is assumed is basic calculus.
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Probabilistic Models

2007
Abstract Financial markets promote mutually beneficial intertemporal exchanges by reducing the costs for individuals to buy and sell financial securities. The securities are rights to receive sequences of future payments. The economics of financial markets is a systematic study of how, and how well, these markets promote mutually ...
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Probabilistic Modeling

2018
Besides using logic-probabilistic analysis for probabilistic estimation itself, it is often necessary to consider uncertain or underdetermined information of a different nature expressed in the following forms: interval estimates, lists of possible options, hypothetical or possibilistic statements, etc. This chapter discusses methods of logic and logic-
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Probabilistic protein homology modeling

2014
Searching sequence databases and building 3D models for proteins are important tasks for biologists. When the structure of a query protein is given, its function can be inferred. However, experimental methods for structure prediction are both expensive and time consuming.
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Building Probabilistic Models

1997
We have seen in Chapter 3 that the knowledge base of a probabilistic expert system consists of a set of variables and a probabilistic model describing the relationships among them. We have also seen that all the information about the relationships among a set of variables is contained in the joint probability distribution (JPD) of the variables.
Enrique Castillo   +2 more
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