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You searched for subject:(Bayesian inference). Showing records 1 – 30 of 629 total matches.

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1. Doraiswamy, Srikrishna. Characterization of Nonlinear Material Response in the Presence of Large Uncertainties ??? A Bayesian Approach.

Degree: 2013, Texas Digital Library

 The aim of the current work is to develop a Bayesian approach to model and simulate the behavior of materials with nonlinear mechanical response in… (more)

Subjects/Keywords: Bayesian inference

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APA (6th Edition):

Doraiswamy, S. (2013). Characterization of Nonlinear Material Response in the Presence of Large Uncertainties ??? A Bayesian Approach. (Thesis). Texas Digital Library. Retrieved from http://hdl.handle.net/1969; http://hdl.handle.net/2249.1/66804

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Doraiswamy, Srikrishna. “Characterization of Nonlinear Material Response in the Presence of Large Uncertainties ??? A Bayesian Approach.” 2013. Thesis, Texas Digital Library. Accessed May 27, 2019. http://hdl.handle.net/1969; http://hdl.handle.net/2249.1/66804.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Doraiswamy, Srikrishna. “Characterization of Nonlinear Material Response in the Presence of Large Uncertainties ??? A Bayesian Approach.” 2013. Web. 27 May 2019.

Vancouver:

Doraiswamy S. Characterization of Nonlinear Material Response in the Presence of Large Uncertainties ??? A Bayesian Approach. [Internet] [Thesis]. Texas Digital Library; 2013. [cited 2019 May 27]. Available from: http://hdl.handle.net/1969; http://hdl.handle.net/2249.1/66804.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Doraiswamy S. Characterization of Nonlinear Material Response in the Presence of Large Uncertainties ??? A Bayesian Approach. [Thesis]. Texas Digital Library; 2013. Available from: http://hdl.handle.net/1969; http://hdl.handle.net/2249.1/66804

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Louisiana State University

2. Bhale, Ishan Singh. Bayesian inference application to burglary detection.

Degree: MSCS, Computer Sciences, 2012, Louisiana State University

 Real time motion tracking is very important for video analytics. But very little research has been done in identifying the top-level plans behind the atomic… (more)

Subjects/Keywords: Bayesian Inference

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APA (6th Edition):

Bhale, I. S. (2012). Bayesian inference application to burglary detection. (Masters Thesis). Louisiana State University. Retrieved from etd-01222013-155000 ; https://digitalcommons.lsu.edu/gradschool_theses/2382

Chicago Manual of Style (16th Edition):

Bhale, Ishan Singh. “Bayesian inference application to burglary detection.” 2012. Masters Thesis, Louisiana State University. Accessed May 27, 2019. etd-01222013-155000 ; https://digitalcommons.lsu.edu/gradschool_theses/2382.

MLA Handbook (7th Edition):

Bhale, Ishan Singh. “Bayesian inference application to burglary detection.” 2012. Web. 27 May 2019.

Vancouver:

Bhale IS. Bayesian inference application to burglary detection. [Internet] [Masters thesis]. Louisiana State University; 2012. [cited 2019 May 27]. Available from: etd-01222013-155000 ; https://digitalcommons.lsu.edu/gradschool_theses/2382.

Council of Science Editors:

Bhale IS. Bayesian inference application to burglary detection. [Masters Thesis]. Louisiana State University; 2012. Available from: etd-01222013-155000 ; https://digitalcommons.lsu.edu/gradschool_theses/2382

3. Sugden, Lauren Alpert. Structure, Variation, and Reproducibility: Bayesian inference in problems arising from the study of RNA and an RNA-binding protein.

Degree: PhD, Applied Mathematics, 2014, Brown University

 Far from being solely a passive messenger between DNA and protein, RNA is a complex molecule involved in regulation at many levels. While the best-known… (more)

Subjects/Keywords: Bayesian inference

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APA (6th Edition):

Sugden, L. A. (2014). Structure, Variation, and Reproducibility: Bayesian inference in problems arising from the study of RNA and an RNA-binding protein. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:386269/

Chicago Manual of Style (16th Edition):

Sugden, Lauren Alpert. “Structure, Variation, and Reproducibility: Bayesian inference in problems arising from the study of RNA and an RNA-binding protein.” 2014. Doctoral Dissertation, Brown University. Accessed May 27, 2019. https://repository.library.brown.edu/studio/item/bdr:386269/.

MLA Handbook (7th Edition):

Sugden, Lauren Alpert. “Structure, Variation, and Reproducibility: Bayesian inference in problems arising from the study of RNA and an RNA-binding protein.” 2014. Web. 27 May 2019.

Vancouver:

Sugden LA. Structure, Variation, and Reproducibility: Bayesian inference in problems arising from the study of RNA and an RNA-binding protein. [Internet] [Doctoral dissertation]. Brown University; 2014. [cited 2019 May 27]. Available from: https://repository.library.brown.edu/studio/item/bdr:386269/.

Council of Science Editors:

Sugden LA. Structure, Variation, and Reproducibility: Bayesian inference in problems arising from the study of RNA and an RNA-binding protein. [Doctoral Dissertation]. Brown University; 2014. Available from: https://repository.library.brown.edu/studio/item/bdr:386269/

4. Lin, Luan. Bayesian Inference and High-D space Characterization with application in Paleoclimatology and Biology.

Degree: PhD, Applied Mathematics, 2012, Brown University

 This thesis is a mathematical study of paleoclimatology and computational biology. Part I gives an introduction and overview of this dissertation. Part II presents the… (more)

Subjects/Keywords: bayesian inference

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APA (6th Edition):

Lin, L. (2012). Bayesian Inference and High-D space Characterization with application in Paleoclimatology and Biology. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:297525/

Chicago Manual of Style (16th Edition):

Lin, Luan. “Bayesian Inference and High-D space Characterization with application in Paleoclimatology and Biology.” 2012. Doctoral Dissertation, Brown University. Accessed May 27, 2019. https://repository.library.brown.edu/studio/item/bdr:297525/.

MLA Handbook (7th Edition):

Lin, Luan. “Bayesian Inference and High-D space Characterization with application in Paleoclimatology and Biology.” 2012. Web. 27 May 2019.

Vancouver:

Lin L. Bayesian Inference and High-D space Characterization with application in Paleoclimatology and Biology. [Internet] [Doctoral dissertation]. Brown University; 2012. [cited 2019 May 27]. Available from: https://repository.library.brown.edu/studio/item/bdr:297525/.

Council of Science Editors:

Lin L. Bayesian Inference and High-D space Characterization with application in Paleoclimatology and Biology. [Doctoral Dissertation]. Brown University; 2012. Available from: https://repository.library.brown.edu/studio/item/bdr:297525/


Texas A&M University

5. Das, Roneet. Probabilistic Slope Stability Assessment of Submarine and Slides by the Use of Bayesian Inference.

Degree: MS, Civil Engineering, 2016, Texas A&M University

 Estimates of probability of slope failure based on Monte-Carlo methods depend upon the state of evidence on the slope stability model parameters. The Bayesian framework… (more)

Subjects/Keywords: Slope Stability; Bayesian Inference

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APA (6th Edition):

Das, R. (2016). Probabilistic Slope Stability Assessment of Submarine and Slides by the Use of Bayesian Inference. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/157070

Chicago Manual of Style (16th Edition):

Das, Roneet. “Probabilistic Slope Stability Assessment of Submarine and Slides by the Use of Bayesian Inference.” 2016. Masters Thesis, Texas A&M University. Accessed May 27, 2019. http://hdl.handle.net/1969.1/157070.

MLA Handbook (7th Edition):

Das, Roneet. “Probabilistic Slope Stability Assessment of Submarine and Slides by the Use of Bayesian Inference.” 2016. Web. 27 May 2019.

Vancouver:

Das R. Probabilistic Slope Stability Assessment of Submarine and Slides by the Use of Bayesian Inference. [Internet] [Masters thesis]. Texas A&M University; 2016. [cited 2019 May 27]. Available from: http://hdl.handle.net/1969.1/157070.

Council of Science Editors:

Das R. Probabilistic Slope Stability Assessment of Submarine and Slides by the Use of Bayesian Inference. [Masters Thesis]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/157070


University of Sydney

6. Abeywardana, Sachinthaka. Variational Inference in Generalised Hyperbolic and von Mises-Fisher Distributions .

Degree: 2015, University of Sydney

 Most real world data are skewed, contain more than the set of real numbers, and have higher probabilities of extreme events occurring compared to a… (more)

Subjects/Keywords: machine learning; Bayesian inference

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APA (6th Edition):

Abeywardana, S. (2015). Variational Inference in Generalised Hyperbolic and von Mises-Fisher Distributions . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/16504

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Abeywardana, Sachinthaka. “Variational Inference in Generalised Hyperbolic and von Mises-Fisher Distributions .” 2015. Thesis, University of Sydney. Accessed May 27, 2019. http://hdl.handle.net/2123/16504.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Abeywardana, Sachinthaka. “Variational Inference in Generalised Hyperbolic and von Mises-Fisher Distributions .” 2015. Web. 27 May 2019.

Vancouver:

Abeywardana S. Variational Inference in Generalised Hyperbolic and von Mises-Fisher Distributions . [Internet] [Thesis]. University of Sydney; 2015. [cited 2019 May 27]. Available from: http://hdl.handle.net/2123/16504.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Abeywardana S. Variational Inference in Generalised Hyperbolic and von Mises-Fisher Distributions . [Thesis]. University of Sydney; 2015. Available from: http://hdl.handle.net/2123/16504

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Sydney

7. McCalman, Lachlan Robert. Function Embeddings for Multi-modal Bayesian Inference .

Degree: 2013, University of Sydney

 Tractable Bayesian inference is a fundamental challenge in robotics and machine learning. Standard approaches such as Gaussian process regression and Kalman filtering make strong Gaussianity… (more)

Subjects/Keywords: Statistics; Inference; Bayesian; Machine Learning

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APA (6th Edition):

McCalman, L. R. (2013). Function Embeddings for Multi-modal Bayesian Inference . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/12031

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

McCalman, Lachlan Robert. “Function Embeddings for Multi-modal Bayesian Inference .” 2013. Thesis, University of Sydney. Accessed May 27, 2019. http://hdl.handle.net/2123/12031.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

McCalman, Lachlan Robert. “Function Embeddings for Multi-modal Bayesian Inference .” 2013. Web. 27 May 2019.

Vancouver:

McCalman LR. Function Embeddings for Multi-modal Bayesian Inference . [Internet] [Thesis]. University of Sydney; 2013. [cited 2019 May 27]. Available from: http://hdl.handle.net/2123/12031.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

McCalman LR. Function Embeddings for Multi-modal Bayesian Inference . [Thesis]. University of Sydney; 2013. Available from: http://hdl.handle.net/2123/12031

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Otago

8. Holmes, Tom. Exploring GPS Signal Data and Position Estimation Through Bayesian Inference .

Degree: 2011, University of Otago

 A new approach to position determination using the Global Positioning System (GPS) has been developed where post processing of ultra-short sequences of captured GPS satellite… (more)

Subjects/Keywords: GPS; Bayesian; Animal Tracking; Inference

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APA (6th Edition):

Holmes, T. (2011). Exploring GPS Signal Data and Position Estimation Through Bayesian Inference . (Masters Thesis). University of Otago. Retrieved from http://hdl.handle.net/10523/2032

Chicago Manual of Style (16th Edition):

Holmes, Tom. “Exploring GPS Signal Data and Position Estimation Through Bayesian Inference .” 2011. Masters Thesis, University of Otago. Accessed May 27, 2019. http://hdl.handle.net/10523/2032.

MLA Handbook (7th Edition):

Holmes, Tom. “Exploring GPS Signal Data and Position Estimation Through Bayesian Inference .” 2011. Web. 27 May 2019.

Vancouver:

Holmes T. Exploring GPS Signal Data and Position Estimation Through Bayesian Inference . [Internet] [Masters thesis]. University of Otago; 2011. [cited 2019 May 27]. Available from: http://hdl.handle.net/10523/2032.

Council of Science Editors:

Holmes T. Exploring GPS Signal Data and Position Estimation Through Bayesian Inference . [Masters Thesis]. University of Otago; 2011. Available from: http://hdl.handle.net/10523/2032


University of Miami

9. Abeyruwan, Saminda Wishwajith. PrOntoLearn: Unsupervised Lexico-Semantic Ontology Generation using Probabilistic Methods.

Degree: MS, Computer Science (Arts and Sciences), 2010, University of Miami

 An ontology is a formal, explicit specification of a shared conceptualization. Formalizing an ontology for a domain is a tedious and cumbersome process. It is… (more)

Subjects/Keywords: An Ontology; Learning; Bayesian Inference

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APA (6th Edition):

Abeyruwan, S. W. (2010). PrOntoLearn: Unsupervised Lexico-Semantic Ontology Generation using Probabilistic Methods. (Thesis). University of Miami. Retrieved from https://scholarlyrepository.miami.edu/oa_theses/28

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Abeyruwan, Saminda Wishwajith. “PrOntoLearn: Unsupervised Lexico-Semantic Ontology Generation using Probabilistic Methods.” 2010. Thesis, University of Miami. Accessed May 27, 2019. https://scholarlyrepository.miami.edu/oa_theses/28.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Abeyruwan, Saminda Wishwajith. “PrOntoLearn: Unsupervised Lexico-Semantic Ontology Generation using Probabilistic Methods.” 2010. Web. 27 May 2019.

Vancouver:

Abeyruwan SW. PrOntoLearn: Unsupervised Lexico-Semantic Ontology Generation using Probabilistic Methods. [Internet] [Thesis]. University of Miami; 2010. [cited 2019 May 27]. Available from: https://scholarlyrepository.miami.edu/oa_theses/28.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Abeyruwan SW. PrOntoLearn: Unsupervised Lexico-Semantic Ontology Generation using Probabilistic Methods. [Thesis]. University of Miami; 2010. Available from: https://scholarlyrepository.miami.edu/oa_theses/28

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Toronto

10. Cheng, Vincent. Modeling the Climatology of Tornado Occurrence using Bayesian Inference.

Degree: PhD, 2014, University of Toronto

 Our mechanistic understanding of tornadic environments has significantly improved by the recent technological enhancements in the detection of tornadoes as well as the advances of… (more)

Subjects/Keywords: Bayesian Inference; Tornadoes; 0368

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APA (6th Edition):

Cheng, V. (2014). Modeling the Climatology of Tornado Occurrence using Bayesian Inference. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/68452

Chicago Manual of Style (16th Edition):

Cheng, Vincent. “Modeling the Climatology of Tornado Occurrence using Bayesian Inference.” 2014. Doctoral Dissertation, University of Toronto. Accessed May 27, 2019. http://hdl.handle.net/1807/68452.

MLA Handbook (7th Edition):

Cheng, Vincent. “Modeling the Climatology of Tornado Occurrence using Bayesian Inference.” 2014. Web. 27 May 2019.

Vancouver:

Cheng V. Modeling the Climatology of Tornado Occurrence using Bayesian Inference. [Internet] [Doctoral dissertation]. University of Toronto; 2014. [cited 2019 May 27]. Available from: http://hdl.handle.net/1807/68452.

Council of Science Editors:

Cheng V. Modeling the Climatology of Tornado Occurrence using Bayesian Inference. [Doctoral Dissertation]. University of Toronto; 2014. Available from: http://hdl.handle.net/1807/68452


University of Alberta

11. Gonzalez, Ruben. Bayesian Methods for On-Line Gross Error Detection and Compensation.

Degree: MS, Department of Chemical and Materials Engineering, 2010, University of Alberta

 Data reconciliation and gross error detection are traditional methods toward detecting mass balance inconsistency within process instrument data. These methods use a static approach for… (more)

Subjects/Keywords: Gross Error Detection; Bayesian Inference; Data Reconciliation

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APA (6th Edition):

Gonzalez, R. (2010). Bayesian Methods for On-Line Gross Error Detection and Compensation. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/w6634487q

Chicago Manual of Style (16th Edition):

Gonzalez, Ruben. “Bayesian Methods for On-Line Gross Error Detection and Compensation.” 2010. Masters Thesis, University of Alberta. Accessed May 27, 2019. https://era.library.ualberta.ca/files/w6634487q.

MLA Handbook (7th Edition):

Gonzalez, Ruben. “Bayesian Methods for On-Line Gross Error Detection and Compensation.” 2010. Web. 27 May 2019.

Vancouver:

Gonzalez R. Bayesian Methods for On-Line Gross Error Detection and Compensation. [Internet] [Masters thesis]. University of Alberta; 2010. [cited 2019 May 27]. Available from: https://era.library.ualberta.ca/files/w6634487q.

Council of Science Editors:

Gonzalez R. Bayesian Methods for On-Line Gross Error Detection and Compensation. [Masters Thesis]. University of Alberta; 2010. Available from: https://era.library.ualberta.ca/files/w6634487q


Princeton University

12. Ranganath, Rajesh. Black Box Variational Inference: Scalable, Generic Bayesian Computation and its Applications .

Degree: PhD, 2017, Princeton University

 Probabilistic generative models are robust to noise, uncover unseen patterns, and make predictions about the future. These models have been used successfully to solve problems… (more)

Subjects/Keywords: Bayesian Statistics; Machine Learning; Variational Inference

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APA (6th Edition):

Ranganath, R. (2017). Black Box Variational Inference: Scalable, Generic Bayesian Computation and its Applications . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01pr76f608w

Chicago Manual of Style (16th Edition):

Ranganath, Rajesh. “Black Box Variational Inference: Scalable, Generic Bayesian Computation and its Applications .” 2017. Doctoral Dissertation, Princeton University. Accessed May 27, 2019. http://arks.princeton.edu/ark:/88435/dsp01pr76f608w.

MLA Handbook (7th Edition):

Ranganath, Rajesh. “Black Box Variational Inference: Scalable, Generic Bayesian Computation and its Applications .” 2017. Web. 27 May 2019.

Vancouver:

Ranganath R. Black Box Variational Inference: Scalable, Generic Bayesian Computation and its Applications . [Internet] [Doctoral dissertation]. Princeton University; 2017. [cited 2019 May 27]. Available from: http://arks.princeton.edu/ark:/88435/dsp01pr76f608w.

Council of Science Editors:

Ranganath R. Black Box Variational Inference: Scalable, Generic Bayesian Computation and its Applications . [Doctoral Dissertation]. Princeton University; 2017. Available from: http://arks.princeton.edu/ark:/88435/dsp01pr76f608w


Baylor University

13. [No author]. Graphical methods in prior elicitation.

Degree: 2017, Baylor University

 Prior elicitation is the process of quantifying an expert's belief in the form of a probability distribution on a parameter(s) to be used in a… (more)

Subjects/Keywords: Bayesian statistics. Prior elicitation. Graphical inference.

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APA (6th Edition):

author], [. (2017). Graphical methods in prior elicitation. (Thesis). Baylor University. Retrieved from http://hdl.handle.net/2104/10111

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

author], [No. “Graphical methods in prior elicitation. ” 2017. Thesis, Baylor University. Accessed May 27, 2019. http://hdl.handle.net/2104/10111.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

author], [No. “Graphical methods in prior elicitation. ” 2017. Web. 27 May 2019.

Vancouver:

author] [. Graphical methods in prior elicitation. [Internet] [Thesis]. Baylor University; 2017. [cited 2019 May 27]. Available from: http://hdl.handle.net/2104/10111.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

author] [. Graphical methods in prior elicitation. [Thesis]. Baylor University; 2017. Available from: http://hdl.handle.net/2104/10111

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Penn State University

14. Tibbits, Matthew McLean. Parallel Multivariate Slice Sampling.

Degree: MS, Statistics, 2009, Penn State University

 Slice sampling provides an easily implemented method for constructing a Markov chain Monte Carlo (MCMC) algorithm. However, slice sampling has two major drawbacks: (i) it… (more)

Subjects/Keywords: Bayesian inference; Markov chain Monte Carlo; Para

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APA (6th Edition):

Tibbits, M. M. (2009). Parallel Multivariate Slice Sampling. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/9151

Chicago Manual of Style (16th Edition):

Tibbits, Matthew McLean. “Parallel Multivariate Slice Sampling.” 2009. Masters Thesis, Penn State University. Accessed May 27, 2019. https://etda.libraries.psu.edu/catalog/9151.

MLA Handbook (7th Edition):

Tibbits, Matthew McLean. “Parallel Multivariate Slice Sampling.” 2009. Web. 27 May 2019.

Vancouver:

Tibbits MM. Parallel Multivariate Slice Sampling. [Internet] [Masters thesis]. Penn State University; 2009. [cited 2019 May 27]. Available from: https://etda.libraries.psu.edu/catalog/9151.

Council of Science Editors:

Tibbits MM. Parallel Multivariate Slice Sampling. [Masters Thesis]. Penn State University; 2009. Available from: https://etda.libraries.psu.edu/catalog/9151


University of Cambridge

15. Graff, Philip B. Bayesian methods for gravitational waves and neural networks.

Degree: PhD, 2012, University of Cambridge

 Einstein’s general theory of relativity has withstood 100 years of testing and will soon be facing one of its toughest challenges. In a few years… (more)

Subjects/Keywords: 530; Bayesian inference; Gravitational waves; Machine learning

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APA (6th Edition):

Graff, P. B. (2012). Bayesian methods for gravitational waves and neural networks. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/244270 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.566190

Chicago Manual of Style (16th Edition):

Graff, Philip B. “Bayesian methods for gravitational waves and neural networks.” 2012. Doctoral Dissertation, University of Cambridge. Accessed May 27, 2019. https://www.repository.cam.ac.uk/handle/1810/244270 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.566190.

MLA Handbook (7th Edition):

Graff, Philip B. “Bayesian methods for gravitational waves and neural networks.” 2012. Web. 27 May 2019.

Vancouver:

Graff PB. Bayesian methods for gravitational waves and neural networks. [Internet] [Doctoral dissertation]. University of Cambridge; 2012. [cited 2019 May 27]. Available from: https://www.repository.cam.ac.uk/handle/1810/244270 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.566190.

Council of Science Editors:

Graff PB. Bayesian methods for gravitational waves and neural networks. [Doctoral Dissertation]. University of Cambridge; 2012. Available from: https://www.repository.cam.ac.uk/handle/1810/244270 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.566190


University of Sydney

16. Babbar, Sakshi. Inferring Anomalies from Data using Bayesian Networks .

Degree: 2013, University of Sydney

 Existing studies on data mining has largely focused on the design of measures and algorithms to identify outliers in large and high dimensional categorical and… (more)

Subjects/Keywords: Bayesian networks; outlier; causal inference; knowledge discovery

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APA (6th Edition):

Babbar, S. (2013). Inferring Anomalies from Data using Bayesian Networks . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/9371

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Babbar, Sakshi. “Inferring Anomalies from Data using Bayesian Networks .” 2013. Thesis, University of Sydney. Accessed May 27, 2019. http://hdl.handle.net/2123/9371.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Babbar, Sakshi. “Inferring Anomalies from Data using Bayesian Networks .” 2013. Web. 27 May 2019.

Vancouver:

Babbar S. Inferring Anomalies from Data using Bayesian Networks . [Internet] [Thesis]. University of Sydney; 2013. [cited 2019 May 27]. Available from: http://hdl.handle.net/2123/9371.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Babbar S. Inferring Anomalies from Data using Bayesian Networks . [Thesis]. University of Sydney; 2013. Available from: http://hdl.handle.net/2123/9371

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Houston

17. Bhardwaj, Manisha 1986-. Visual decision making in the presence of stimulus and measurement correlations.

Degree: Mathematics, Department of, 2013, University of Houston

 Our brains process sensory information to infer the state of the world. However, the input from our senses is noisy, which may lead to errors… (more)

Subjects/Keywords: Bayesian inference; model comparison; correlations; target detection

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Bhardwaj, M. 1. (2013). Visual decision making in the presence of stimulus and measurement correlations. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/1239

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Bhardwaj, Manisha 1986-. “Visual decision making in the presence of stimulus and measurement correlations.” 2013. Thesis, University of Houston. Accessed May 27, 2019. http://hdl.handle.net/10657/1239.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Bhardwaj, Manisha 1986-. “Visual decision making in the presence of stimulus and measurement correlations.” 2013. Web. 27 May 2019.

Vancouver:

Bhardwaj M1. Visual decision making in the presence of stimulus and measurement correlations. [Internet] [Thesis]. University of Houston; 2013. [cited 2019 May 27]. Available from: http://hdl.handle.net/10657/1239.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bhardwaj M1. Visual decision making in the presence of stimulus and measurement correlations. [Thesis]. University of Houston; 2013. Available from: http://hdl.handle.net/10657/1239

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Cambridge

18. Jin, Yingyan. Supervised learning for back analysis of excavations in the observational method.

Degree: PhD, 2018, University of Cambridge

 In the past few decades, demand for construction in underground spaces has increased dramatically in urban areas with high population densities. However, the impact of… (more)

Subjects/Keywords: Bayesian inference; Excavations; Observational method; Back analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Jin, Y. (2018). Supervised learning for back analysis of excavations in the observational method. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/275587 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744808

Chicago Manual of Style (16th Edition):

Jin, Yingyan. “Supervised learning for back analysis of excavations in the observational method.” 2018. Doctoral Dissertation, University of Cambridge. Accessed May 27, 2019. https://www.repository.cam.ac.uk/handle/1810/275587 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744808.

MLA Handbook (7th Edition):

Jin, Yingyan. “Supervised learning for back analysis of excavations in the observational method.” 2018. Web. 27 May 2019.

Vancouver:

Jin Y. Supervised learning for back analysis of excavations in the observational method. [Internet] [Doctoral dissertation]. University of Cambridge; 2018. [cited 2019 May 27]. Available from: https://www.repository.cam.ac.uk/handle/1810/275587 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744808.

Council of Science Editors:

Jin Y. Supervised learning for back analysis of excavations in the observational method. [Doctoral Dissertation]. University of Cambridge; 2018. Available from: https://www.repository.cam.ac.uk/handle/1810/275587 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744808


Cornell University

19. Wan, Muting. Model-Based Classification With Applications To High-Dimensional Data In Bioinformatics .

Degree: 2015, Cornell University

 In recent years, sparse classification problems have emerged in many fields of study. Finite mixture models have been developed to facilitate Bayesian inference where parameter… (more)

Subjects/Keywords: Bayesian inference; Linear mixed models; Bioinformatics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wan, M. (2015). Model-Based Classification With Applications To High-Dimensional Data In Bioinformatics . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/39389

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wan, Muting. “Model-Based Classification With Applications To High-Dimensional Data In Bioinformatics .” 2015. Thesis, Cornell University. Accessed May 27, 2019. http://hdl.handle.net/1813/39389.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wan, Muting. “Model-Based Classification With Applications To High-Dimensional Data In Bioinformatics .” 2015. Web. 27 May 2019.

Vancouver:

Wan M. Model-Based Classification With Applications To High-Dimensional Data In Bioinformatics . [Internet] [Thesis]. Cornell University; 2015. [cited 2019 May 27]. Available from: http://hdl.handle.net/1813/39389.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wan M. Model-Based Classification With Applications To High-Dimensional Data In Bioinformatics . [Thesis]. Cornell University; 2015. Available from: http://hdl.handle.net/1813/39389

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Texas – Austin

20. Zhang, Michael Minyi. Scalable inference for Bayesian non-parametrics.

Degree: Statistics, 2018, University of Texas – Austin

Bayesian non-parametric models, despite their theoretical elegance, face a serious computational burden that prevents their use in serious "big data'' scenarios. Furthermore, we cannot expect… (more)

Subjects/Keywords: Bayesian non-parametrics; Scalable inference; Machine learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zhang, M. M. (2018). Scalable inference for Bayesian non-parametrics. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/65734

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Zhang, Michael Minyi. “Scalable inference for Bayesian non-parametrics.” 2018. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/65734.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Zhang, Michael Minyi. “Scalable inference for Bayesian non-parametrics.” 2018. Web. 27 May 2019.

Vancouver:

Zhang MM. Scalable inference for Bayesian non-parametrics. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/65734.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhang MM. Scalable inference for Bayesian non-parametrics. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/65734

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Texas – Austin

21. Gillett, Carlos Townes. A comparison of two Markov Chain Monte Carlo methods for sampling from unnormalized discrete distributions.

Degree: Statistics, 2015, University of Texas – Austin

 This report compares the convergence behavior of the Metropolis-Hastings and an alternative Markov Chain Monte Carlo sampling algorithm targeting unnormalized, discrete distributions with countably infinite… (more)

Subjects/Keywords: Metropolis-Hastings; Bayesian inference; Unnormalized probabilities

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Gillett, C. T. (2015). A comparison of two Markov Chain Monte Carlo methods for sampling from unnormalized discrete distributions. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32494

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Gillett, Carlos Townes. “A comparison of two Markov Chain Monte Carlo methods for sampling from unnormalized discrete distributions.” 2015. Thesis, University of Texas – Austin. Accessed May 27, 2019. http://hdl.handle.net/2152/32494.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Gillett, Carlos Townes. “A comparison of two Markov Chain Monte Carlo methods for sampling from unnormalized discrete distributions.” 2015. Web. 27 May 2019.

Vancouver:

Gillett CT. A comparison of two Markov Chain Monte Carlo methods for sampling from unnormalized discrete distributions. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 May 27]. Available from: http://hdl.handle.net/2152/32494.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gillett CT. A comparison of two Markov Chain Monte Carlo methods for sampling from unnormalized discrete distributions. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32494

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


North Carolina State University

22. DiCasoli, Carl Matthew. Bayesian Regression Methods for Crossing Survival Curves.

Degree: PhD, Statistics, 2009, North Carolina State University

 In survival data analysis, the proportional hazards (PH), accelerated failure time (AFT), and proportional odds (PO) models are commonly used semiparametric models for the comparison… (more)

Subjects/Keywords: variational methods; Bayesian inference; survival analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

DiCasoli, C. M. (2009). Bayesian Regression Methods for Crossing Survival Curves. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/4743

Chicago Manual of Style (16th Edition):

DiCasoli, Carl Matthew. “Bayesian Regression Methods for Crossing Survival Curves.” 2009. Doctoral Dissertation, North Carolina State University. Accessed May 27, 2019. http://www.lib.ncsu.edu/resolver/1840.16/4743.

MLA Handbook (7th Edition):

DiCasoli, Carl Matthew. “Bayesian Regression Methods for Crossing Survival Curves.” 2009. Web. 27 May 2019.

Vancouver:

DiCasoli CM. Bayesian Regression Methods for Crossing Survival Curves. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2019 May 27]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4743.

Council of Science Editors:

DiCasoli CM. Bayesian Regression Methods for Crossing Survival Curves. [Doctoral Dissertation]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4743

23. Feldman, Naomi H. Interactions between word and speech sound categorization in language acquisition.

Degree: PhD, Cognitive Sciences, 2011, Brown University

 Infants learn to segment words from fluent speech during the same period as they learn native language phonetic categories, yet accounts of phonetic category acquisition… (more)

Subjects/Keywords: language acquisition; phonetic category learning; Bayesian inference

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Feldman, N. H. (2011). Interactions between word and speech sound categorization in language acquisition. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:11219/

Chicago Manual of Style (16th Edition):

Feldman, Naomi H. “Interactions between word and speech sound categorization in language acquisition.” 2011. Doctoral Dissertation, Brown University. Accessed May 27, 2019. https://repository.library.brown.edu/studio/item/bdr:11219/.

MLA Handbook (7th Edition):

Feldman, Naomi H. “Interactions between word and speech sound categorization in language acquisition.” 2011. Web. 27 May 2019.

Vancouver:

Feldman NH. Interactions between word and speech sound categorization in language acquisition. [Internet] [Doctoral dissertation]. Brown University; 2011. [cited 2019 May 27]. Available from: https://repository.library.brown.edu/studio/item/bdr:11219/.

Council of Science Editors:

Feldman NH. Interactions between word and speech sound categorization in language acquisition. [Doctoral Dissertation]. Brown University; 2011. Available from: https://repository.library.brown.edu/studio/item/bdr:11219/


University of Cambridge

24. Matthews, Alexander Graeme de Garis. Scalable Gaussian process inference using variational methods.

Degree: PhD, 2017, University of Cambridge

 Gaussian processes can be used as priors on functions. The need for a flexible, principled, probabilistic model of functional relations is common in practice. Consequently,… (more)

Subjects/Keywords: Gaussian process; Variational inference; Machine learning; Statistics; Bayesian inference

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Matthews, A. G. d. G. (2017). Scalable Gaussian process inference using variational methods. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/278022 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.753312

Chicago Manual of Style (16th Edition):

Matthews, Alexander Graeme de Garis. “Scalable Gaussian process inference using variational methods.” 2017. Doctoral Dissertation, University of Cambridge. Accessed May 27, 2019. https://www.repository.cam.ac.uk/handle/1810/278022 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.753312.

MLA Handbook (7th Edition):

Matthews, Alexander Graeme de Garis. “Scalable Gaussian process inference using variational methods.” 2017. Web. 27 May 2019.

Vancouver:

Matthews AGdG. Scalable Gaussian process inference using variational methods. [Internet] [Doctoral dissertation]. University of Cambridge; 2017. [cited 2019 May 27]. Available from: https://www.repository.cam.ac.uk/handle/1810/278022 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.753312.

Council of Science Editors:

Matthews AGdG. Scalable Gaussian process inference using variational methods. [Doctoral Dissertation]. University of Cambridge; 2017. Available from: https://www.repository.cam.ac.uk/handle/1810/278022 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.753312


University of Waterloo

25. Hincks, Ian. Exploring Practical Methodologies for the Characterization and Control of Small Quantum Systems.

Degree: 2018, University of Waterloo

 We explore methodologies for characterizing and controlling small quantum systems. We are interested in starting with a description of a quantum system, designing estimators for… (more)

Subjects/Keywords: quantum; quantum control; quantum information; bayesian inference; benchmarking; quantum characterization; inference

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hincks, I. (2018). Exploring Practical Methodologies for the Characterization and Control of Small Quantum Systems. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13711

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hincks, Ian. “Exploring Practical Methodologies for the Characterization and Control of Small Quantum Systems.” 2018. Thesis, University of Waterloo. Accessed May 27, 2019. http://hdl.handle.net/10012/13711.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hincks, Ian. “Exploring Practical Methodologies for the Characterization and Control of Small Quantum Systems.” 2018. Web. 27 May 2019.

Vancouver:

Hincks I. Exploring Practical Methodologies for the Characterization and Control of Small Quantum Systems. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2019 May 27]. Available from: http://hdl.handle.net/10012/13711.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hincks I. Exploring Practical Methodologies for the Characterization and Control of Small Quantum Systems. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13711

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Australian National University

26. Dawkins, Mark Walter. Melded Bayesian Inference for Stochastic Theoretical Models with Applications in Agent Based Modelling .

Degree: 2017, Australian National University

Bayesian melding is extended for applications to stochastic theoretical models. Agent Based models, a class of stochastic theoretical models, are investigated and it is found… (more)

Subjects/Keywords: Bayesian Melding; Bayesian Inference; Agent Based Modelling; Simulation; Stochastic Modelling

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APA (6th Edition):

Dawkins, M. W. (2017). Melded Bayesian Inference for Stochastic Theoretical Models with Applications in Agent Based Modelling . (Thesis). Australian National University. Retrieved from http://hdl.handle.net/1885/147060

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Dawkins, Mark Walter. “Melded Bayesian Inference for Stochastic Theoretical Models with Applications in Agent Based Modelling .” 2017. Thesis, Australian National University. Accessed May 27, 2019. http://hdl.handle.net/1885/147060.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Dawkins, Mark Walter. “Melded Bayesian Inference for Stochastic Theoretical Models with Applications in Agent Based Modelling .” 2017. Web. 27 May 2019.

Vancouver:

Dawkins MW. Melded Bayesian Inference for Stochastic Theoretical Models with Applications in Agent Based Modelling . [Internet] [Thesis]. Australian National University; 2017. [cited 2019 May 27]. Available from: http://hdl.handle.net/1885/147060.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Dawkins MW. Melded Bayesian Inference for Stochastic Theoretical Models with Applications in Agent Based Modelling . [Thesis]. Australian National University; 2017. Available from: http://hdl.handle.net/1885/147060

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

27. Chen, Ting. Estimation and Detection of Multivariate Gene Regulatory Relationships.

Degree: 2013, Texas A&M University

 The Coefficient of Determination (CoD) plays an important role in Genomics problems, for instance, in the inference of gene regulatory networks from gene- expression data.… (more)

Subjects/Keywords: Coefficient of Determination; Frequentist Inference; Maximum-Likelihood Estimation; Multiple Testing Procedures; Bayesian Inference

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APA (6th Edition):

Chen, T. (2013). Estimation and Detection of Multivariate Gene Regulatory Relationships. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/151702

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chen, Ting. “Estimation and Detection of Multivariate Gene Regulatory Relationships.” 2013. Thesis, Texas A&M University. Accessed May 27, 2019. http://hdl.handle.net/1969.1/151702.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chen, Ting. “Estimation and Detection of Multivariate Gene Regulatory Relationships.” 2013. Web. 27 May 2019.

Vancouver:

Chen T. Estimation and Detection of Multivariate Gene Regulatory Relationships. [Internet] [Thesis]. Texas A&M University; 2013. [cited 2019 May 27]. Available from: http://hdl.handle.net/1969.1/151702.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chen T. Estimation and Detection of Multivariate Gene Regulatory Relationships. [Thesis]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/151702

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Cambridge

28. Jin, Junyang. Novel methods for biological network inference : an application to circadian Ca2+ signaling network.

Degree: PhD, 2018, University of Cambridge

 Biological processes involve complex biochemical interactions among a large number of species like cells, RNA, proteins and metabolites. Learning these interactions is essential to interfering… (more)

Subjects/Keywords: systems biology; network inference; system identification; sparse networks; machine learning; Bayesian inference

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APA (6th Edition):

Jin, J. (2018). Novel methods for biological network inference : an application to circadian Ca2+ signaling network. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/285323 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763710

Chicago Manual of Style (16th Edition):

Jin, Junyang. “Novel methods for biological network inference : an application to circadian Ca2+ signaling network.” 2018. Doctoral Dissertation, University of Cambridge. Accessed May 27, 2019. https://www.repository.cam.ac.uk/handle/1810/285323 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763710.

MLA Handbook (7th Edition):

Jin, Junyang. “Novel methods for biological network inference : an application to circadian Ca2+ signaling network.” 2018. Web. 27 May 2019.

Vancouver:

Jin J. Novel methods for biological network inference : an application to circadian Ca2+ signaling network. [Internet] [Doctoral dissertation]. University of Cambridge; 2018. [cited 2019 May 27]. Available from: https://www.repository.cam.ac.uk/handle/1810/285323 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763710.

Council of Science Editors:

Jin J. Novel methods for biological network inference : an application to circadian Ca2+ signaling network. [Doctoral Dissertation]. University of Cambridge; 2018. Available from: https://www.repository.cam.ac.uk/handle/1810/285323 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763710


EPFL

29. Ağir, Berker. Context and Semantic Aware Location Privacy.

Degree: 2016, EPFL

 With ever-increasing computational power, and improved sensing and communication capabilities, smart devices have altered and enhanced the way we process, perceive and interact with information.… (more)

Subjects/Keywords: location privacy; privacy concerns; location semantics; mobile applications; privacy sensitivities; inference attacks; bayesian inference; bayesian networks

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ağir, B. (2016). Context and Semantic Aware Location Privacy. (Thesis). EPFL. Retrieved from http://infoscience.epfl.ch/record/219121

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ağir, Berker. “Context and Semantic Aware Location Privacy.” 2016. Thesis, EPFL. Accessed May 27, 2019. http://infoscience.epfl.ch/record/219121.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ağir, Berker. “Context and Semantic Aware Location Privacy.” 2016. Web. 27 May 2019.

Vancouver:

Ağir B. Context and Semantic Aware Location Privacy. [Internet] [Thesis]. EPFL; 2016. [cited 2019 May 27]. Available from: http://infoscience.epfl.ch/record/219121.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ağir B. Context and Semantic Aware Location Privacy. [Thesis]. EPFL; 2016. Available from: http://infoscience.epfl.ch/record/219121

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Helsinki

30. Jälkö, Joonas. Privacy-aware variational inference.

Degree: Department of Mathematics and Statistics; Helsingfors universitet, Matematisk-naturvetenskapliga fakulteten, Institutionen för matematik och statistik, 2017, University of Helsinki

 This thesis focuses on privacy-preserving statistical inference. We use a probabilistic point of view of privacy called differential privacy. Differential privacy ensures that replacing one… (more)

Subjects/Keywords: Differential privacy; Variational Bayesian methods; Machine learning; Bayesian inference; Tillämpad matematik; Applied Mathematics; Soveltava matematiikka; Differential privacy; Variational Bayesian methods; Machine learning; Bayesian inference

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Jälkö, J. (2017). Privacy-aware variational inference. (Masters Thesis). University of Helsinki. Retrieved from http://hdl.handle.net/10138/228858

Chicago Manual of Style (16th Edition):

Jälkö, Joonas. “Privacy-aware variational inference.” 2017. Masters Thesis, University of Helsinki. Accessed May 27, 2019. http://hdl.handle.net/10138/228858.

MLA Handbook (7th Edition):

Jälkö, Joonas. “Privacy-aware variational inference.” 2017. Web. 27 May 2019.

Vancouver:

Jälkö J. Privacy-aware variational inference. [Internet] [Masters thesis]. University of Helsinki; 2017. [cited 2019 May 27]. Available from: http://hdl.handle.net/10138/228858.

Council of Science Editors:

Jälkö J. Privacy-aware variational inference. [Masters Thesis]. University of Helsinki; 2017. Available from: http://hdl.handle.net/10138/228858

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