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You searched for subject:(graphical model). Showing records 1 – 30 of 178 total matches.

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University of Alberta

1. Sen, Abhishek. Hand Tracking by Fusion of Color and a Range Sensor.

Degree: MS, Department of Computing Science, 2012, University of Alberta

 In this work we have developed a decentralized algorithm for efficient localization and tracking of hands from a sequence of depth and colour images. We… (more)

Subjects/Keywords: hand tracking; graphical model

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APA (6th Edition):

Sen, A. (2012). Hand Tracking by Fusion of Color and a Range Sensor. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/pv63g128r

Chicago Manual of Style (16th Edition):

Sen, Abhishek. “Hand Tracking by Fusion of Color and a Range Sensor.” 2012. Masters Thesis, University of Alberta. Accessed May 08, 2021. https://era.library.ualberta.ca/files/pv63g128r.

MLA Handbook (7th Edition):

Sen, Abhishek. “Hand Tracking by Fusion of Color and a Range Sensor.” 2012. Web. 08 May 2021.

Vancouver:

Sen A. Hand Tracking by Fusion of Color and a Range Sensor. [Internet] [Masters thesis]. University of Alberta; 2012. [cited 2021 May 08]. Available from: https://era.library.ualberta.ca/files/pv63g128r.

Council of Science Editors:

Sen A. Hand Tracking by Fusion of Color and a Range Sensor. [Masters Thesis]. University of Alberta; 2012. Available from: https://era.library.ualberta.ca/files/pv63g128r


University of Rochester

2. LaCombe, Jason R. Non-Informative Priors for Structural Inference in Bayesian Networks.

Degree: PhD, 2011, University of Rochester

 A fundamental problem in multivariate statistics is the determination of dependency relationships among random variables. Bayesian networks equate the dependency properties of the considered variables… (more)

Subjects/Keywords: Bayesian-Networks; Model-Selection; Prior Graphical Model

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APA (6th Edition):

LaCombe, J. R. (2011). Non-Informative Priors for Structural Inference in Bayesian Networks. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/15981

Chicago Manual of Style (16th Edition):

LaCombe, Jason R. “Non-Informative Priors for Structural Inference in Bayesian Networks.” 2011. Doctoral Dissertation, University of Rochester. Accessed May 08, 2021. http://hdl.handle.net/1802/15981.

MLA Handbook (7th Edition):

LaCombe, Jason R. “Non-Informative Priors for Structural Inference in Bayesian Networks.” 2011. Web. 08 May 2021.

Vancouver:

LaCombe JR. Non-Informative Priors for Structural Inference in Bayesian Networks. [Internet] [Doctoral dissertation]. University of Rochester; 2011. [cited 2021 May 08]. Available from: http://hdl.handle.net/1802/15981.

Council of Science Editors:

LaCombe JR. Non-Informative Priors for Structural Inference in Bayesian Networks. [Doctoral Dissertation]. University of Rochester; 2011. Available from: http://hdl.handle.net/1802/15981


Boston University

3. Kang, Xinyu. Statistical methods for topology inference, denoising, and bootstrapping in networks.

Degree: PhD, Mathematics & Statistics, 2018, Boston University

 Quite often, the data we observe can be effectively represented using graphs. The underlying structure of the resulting graph, however, might contain noise and does… (more)

Subjects/Keywords: Statistics; Network; Graphical model; Multiscale modeling

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APA (6th Edition):

Kang, X. (2018). Statistical methods for topology inference, denoising, and bootstrapping in networks. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/33117

Chicago Manual of Style (16th Edition):

Kang, Xinyu. “Statistical methods for topology inference, denoising, and bootstrapping in networks.” 2018. Doctoral Dissertation, Boston University. Accessed May 08, 2021. http://hdl.handle.net/2144/33117.

MLA Handbook (7th Edition):

Kang, Xinyu. “Statistical methods for topology inference, denoising, and bootstrapping in networks.” 2018. Web. 08 May 2021.

Vancouver:

Kang X. Statistical methods for topology inference, denoising, and bootstrapping in networks. [Internet] [Doctoral dissertation]. Boston University; 2018. [cited 2021 May 08]. Available from: http://hdl.handle.net/2144/33117.

Council of Science Editors:

Kang X. Statistical methods for topology inference, denoising, and bootstrapping in networks. [Doctoral Dissertation]. Boston University; 2018. Available from: http://hdl.handle.net/2144/33117


University of Missouri – Columbia

4. Liang, Ye. Bayesian methods on selected topics.

Degree: 2012, University of Missouri – Columbia

 Bayesian methods are widely adopted nowadays in statistical analysis. It is especially useful for the statistical inference of complex models or hierarchical models, for which… (more)

Subjects/Keywords: Bayesian statistics; spatial statistics; epidemiology; graphical model

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APA (6th Edition):

Liang, Y. (2012). Bayesian methods on selected topics. (Thesis). University of Missouri – Columbia. Retrieved from http://hdl.handle.net/10355/15884

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):

Liang, Ye. “Bayesian methods on selected topics.” 2012. Thesis, University of Missouri – Columbia. Accessed May 08, 2021. http://hdl.handle.net/10355/15884.

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

MLA Handbook (7th Edition):

Liang, Ye. “Bayesian methods on selected topics.” 2012. Web. 08 May 2021.

Vancouver:

Liang Y. Bayesian methods on selected topics. [Internet] [Thesis]. University of Missouri – Columbia; 2012. [cited 2021 May 08]. Available from: http://hdl.handle.net/10355/15884.

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

Council of Science Editors:

Liang Y. Bayesian methods on selected topics. [Thesis]. University of Missouri – Columbia; 2012. Available from: http://hdl.handle.net/10355/15884

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


University of New South Wales

5. Liu, Xianghang. New Algorithms for Graphical Models and Their Applications in Learning.

Degree: Computer Science & Engineering, 2015, University of New South Wales

 Probabilistic graphical models bring together graph theory and probability theory in a powerful formalism for multivariate statistical modelling. Since many machine learning problems involve the… (more)

Subjects/Keywords: statistical inference; machine learning; graphical model

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APA (6th Edition):

Liu, X. (2015). New Algorithms for Graphical Models and Their Applications in Learning. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Liu, Xianghang. “New Algorithms for Graphical Models and Their Applications in Learning.” 2015. Doctoral Dissertation, University of New South Wales. Accessed May 08, 2021. http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true.

MLA Handbook (7th Edition):

Liu, Xianghang. “New Algorithms for Graphical Models and Their Applications in Learning.” 2015. Web. 08 May 2021.

Vancouver:

Liu X. New Algorithms for Graphical Models and Their Applications in Learning. [Internet] [Doctoral dissertation]. University of New South Wales; 2015. [cited 2021 May 08]. Available from: http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true.

Council of Science Editors:

Liu X. New Algorithms for Graphical Models and Their Applications in Learning. [Doctoral Dissertation]. University of New South Wales; 2015. Available from: http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true


Virginia Tech

6. Zhang, Yafei. Variable screening and graphical modeling for ultra-high dimensional longitudinal data.

Degree: PhD, Statistics, 2019, Virginia Tech

 Ultrahigh-dimensional variable selection is of great importance in the statistical research. And independence screening is a powerful tool to select important variable when there are… (more)

Subjects/Keywords: graphical model; variable screening; longitudinal data analysis

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APA (6th Edition):

Zhang, Y. (2019). Variable screening and graphical modeling for ultra-high dimensional longitudinal data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/101662

Chicago Manual of Style (16th Edition):

Zhang, Yafei. “Variable screening and graphical modeling for ultra-high dimensional longitudinal data.” 2019. Doctoral Dissertation, Virginia Tech. Accessed May 08, 2021. http://hdl.handle.net/10919/101662.

MLA Handbook (7th Edition):

Zhang, Yafei. “Variable screening and graphical modeling for ultra-high dimensional longitudinal data.” 2019. Web. 08 May 2021.

Vancouver:

Zhang Y. Variable screening and graphical modeling for ultra-high dimensional longitudinal data. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 May 08]. Available from: http://hdl.handle.net/10919/101662.

Council of Science Editors:

Zhang Y. Variable screening and graphical modeling for ultra-high dimensional longitudinal data. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/101662


Texas A&M University

7. Fulford, David Steven. Use of Bayesian Probabilistic Graphical Models for Simultaneous Variable Rate / Variable Pressure-Drop Deconvolution of Single Well and Multi-Well Cases.

Degree: MS, Petroleum Engineering, 2020, Texas A&M University

 Deconvolution is a useful tool for removing of the effects of non-constant production rate on the observed flowing pressures, or the effects of non-constant flowing… (more)

Subjects/Keywords: deconvolution; bayesian; probabilistic graphical model; reservoir analysis

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APA (6th Edition):

Fulford, D. S. (2020). Use of Bayesian Probabilistic Graphical Models for Simultaneous Variable Rate / Variable Pressure-Drop Deconvolution of Single Well and Multi-Well Cases. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/191638

Chicago Manual of Style (16th Edition):

Fulford, David Steven. “Use of Bayesian Probabilistic Graphical Models for Simultaneous Variable Rate / Variable Pressure-Drop Deconvolution of Single Well and Multi-Well Cases.” 2020. Masters Thesis, Texas A&M University. Accessed May 08, 2021. http://hdl.handle.net/1969.1/191638.

MLA Handbook (7th Edition):

Fulford, David Steven. “Use of Bayesian Probabilistic Graphical Models for Simultaneous Variable Rate / Variable Pressure-Drop Deconvolution of Single Well and Multi-Well Cases.” 2020. Web. 08 May 2021.

Vancouver:

Fulford DS. Use of Bayesian Probabilistic Graphical Models for Simultaneous Variable Rate / Variable Pressure-Drop Deconvolution of Single Well and Multi-Well Cases. [Internet] [Masters thesis]. Texas A&M University; 2020. [cited 2021 May 08]. Available from: http://hdl.handle.net/1969.1/191638.

Council of Science Editors:

Fulford DS. Use of Bayesian Probabilistic Graphical Models for Simultaneous Variable Rate / Variable Pressure-Drop Deconvolution of Single Well and Multi-Well Cases. [Masters Thesis]. Texas A&M University; 2020. Available from: http://hdl.handle.net/1969.1/191638


University of California – Irvine

8. Ping, Wei. Learning and Inference in Latent Variable Graphical Models.

Degree: Computer Science, 2016, University of California – Irvine

 Probabilistic graphical models such as Markov random fields provide a powerful framework and tools for machine learning, especially for structured output learning. Latent variables naturally… (more)

Subjects/Keywords: Computer science; Dual-decomposition; Graphical Model; Latent Variable Model; Structured SVM

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APA (6th Edition):

Ping, W. (2016). Learning and Inference in Latent Variable Graphical Models. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/7q90z4b5

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):

Ping, Wei. “Learning and Inference in Latent Variable Graphical Models.” 2016. Thesis, University of California – Irvine. Accessed May 08, 2021. http://www.escholarship.org/uc/item/7q90z4b5.

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

MLA Handbook (7th Edition):

Ping, Wei. “Learning and Inference in Latent Variable Graphical Models.” 2016. Web. 08 May 2021.

Vancouver:

Ping W. Learning and Inference in Latent Variable Graphical Models. [Internet] [Thesis]. University of California – Irvine; 2016. [cited 2021 May 08]. Available from: http://www.escholarship.org/uc/item/7q90z4b5.

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

Council of Science Editors:

Ping W. Learning and Inference in Latent Variable Graphical Models. [Thesis]. University of California – Irvine; 2016. Available from: http://www.escholarship.org/uc/item/7q90z4b5

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


Penn State University

9. Lee, Sanghack. Causal Discovery from Relational Data: Theory and Practice.

Degree: 2018, Penn State University

 Discovery of causal relationships from observational and experimental data is a central problem with applications across multiple areas of scientific endeavor. There has been considerable… (more)

Subjects/Keywords: Causality; Causal Model; Graphical Models; Relational Data; Relational Model

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APA (6th Edition):

Lee, S. (2018). Causal Discovery from Relational Data: Theory and Practice. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/14976sxl439

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):

Lee, Sanghack. “Causal Discovery from Relational Data: Theory and Practice.” 2018. Thesis, Penn State University. Accessed May 08, 2021. https://submit-etda.libraries.psu.edu/catalog/14976sxl439.

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

MLA Handbook (7th Edition):

Lee, Sanghack. “Causal Discovery from Relational Data: Theory and Practice.” 2018. Web. 08 May 2021.

Vancouver:

Lee S. Causal Discovery from Relational Data: Theory and Practice. [Internet] [Thesis]. Penn State University; 2018. [cited 2021 May 08]. Available from: https://submit-etda.libraries.psu.edu/catalog/14976sxl439.

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

Council of Science Editors:

Lee S. Causal Discovery from Relational Data: Theory and Practice. [Thesis]. Penn State University; 2018. Available from: https://submit-etda.libraries.psu.edu/catalog/14976sxl439

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


Brigham Young University

10. Webb, Matthew Aaron. Modeling Individual Health Care Utilization.

Degree: MS, 2016, Brigham Young University

 Health care represents an increasing proportion of global consumption. We discuss ways to model health care utilization on an individual basis. We present a probabilistic,… (more)

Subjects/Keywords: health care; health insurance; generative model; graphical model; Mathematics

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APA (6th Edition):

Webb, M. A. (2016). Modeling Individual Health Care Utilization. (Masters Thesis). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=9841&context=etd

Chicago Manual of Style (16th Edition):

Webb, Matthew Aaron. “Modeling Individual Health Care Utilization.” 2016. Masters Thesis, Brigham Young University. Accessed May 08, 2021. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=9841&context=etd.

MLA Handbook (7th Edition):

Webb, Matthew Aaron. “Modeling Individual Health Care Utilization.” 2016. Web. 08 May 2021.

Vancouver:

Webb MA. Modeling Individual Health Care Utilization. [Internet] [Masters thesis]. Brigham Young University; 2016. [cited 2021 May 08]. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=9841&context=etd.

Council of Science Editors:

Webb MA. Modeling Individual Health Care Utilization. [Masters Thesis]. Brigham Young University; 2016. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=9841&context=etd


Purdue University

11. Li, Yunfan. A study of the prediction performance and multivariate extensions of the horseshoe estimator.

Degree: Statistics, 2019, Purdue University

 The horseshoe prior has been shown to successfully handle high-dimensional sparse estimation problems. It both adapts to sparsity efficiently and provides nearly unbiased estimates for… (more)

Subjects/Keywords: Statistics; Bayesian statistical model; multivariate analysis; Gaussian graphical model (GGM)

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APA (6th Edition):

Li, Y. (2019). A study of the prediction performance and multivariate extensions of the horseshoe estimator. (Thesis). Purdue University. Retrieved from http://hdl.handle.net/10.25394/pgs.8029262.v1

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):

Li, Yunfan. “A study of the prediction performance and multivariate extensions of the horseshoe estimator.” 2019. Thesis, Purdue University. Accessed May 08, 2021. http://hdl.handle.net/10.25394/pgs.8029262.v1.

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

MLA Handbook (7th Edition):

Li, Yunfan. “A study of the prediction performance and multivariate extensions of the horseshoe estimator.” 2019. Web. 08 May 2021.

Vancouver:

Li Y. A study of the prediction performance and multivariate extensions of the horseshoe estimator. [Internet] [Thesis]. Purdue University; 2019. [cited 2021 May 08]. Available from: http://hdl.handle.net/10.25394/pgs.8029262.v1.

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

Council of Science Editors:

Li Y. A study of the prediction performance and multivariate extensions of the horseshoe estimator. [Thesis]. Purdue University; 2019. Available from: http://hdl.handle.net/10.25394/pgs.8029262.v1

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


Delft University of Technology

12. Cueto Fernandez, Judith (author). Joint angle coupling of a musculoskeletal model and a graphical model of the hand for enhanced display in medical education.

Degree: 2020, Delft University of Technology

Advanced anatomical knowledge and understanding of the muscles involved in various movements are crucial for medical practitioners to reach the correct diagnostic and successfully predict… (more)

Subjects/Keywords: Hand Model; Musculoskeletal Model; Graphical Model; Inverse Kinematics; Motion Capture; Joints; Finger

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APA (6th Edition):

Cueto Fernandez, J. (. (2020). Joint angle coupling of a musculoskeletal model and a graphical model of the hand for enhanced display in medical education. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:02cc8ccb-33ae-4b07-a402-ac5baf3ec365

Chicago Manual of Style (16th Edition):

Cueto Fernandez, Judith (author). “Joint angle coupling of a musculoskeletal model and a graphical model of the hand for enhanced display in medical education.” 2020. Masters Thesis, Delft University of Technology. Accessed May 08, 2021. http://resolver.tudelft.nl/uuid:02cc8ccb-33ae-4b07-a402-ac5baf3ec365.

MLA Handbook (7th Edition):

Cueto Fernandez, Judith (author). “Joint angle coupling of a musculoskeletal model and a graphical model of the hand for enhanced display in medical education.” 2020. Web. 08 May 2021.

Vancouver:

Cueto Fernandez J(. Joint angle coupling of a musculoskeletal model and a graphical model of the hand for enhanced display in medical education. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 May 08]. Available from: http://resolver.tudelft.nl/uuid:02cc8ccb-33ae-4b07-a402-ac5baf3ec365.

Council of Science Editors:

Cueto Fernandez J(. Joint angle coupling of a musculoskeletal model and a graphical model of the hand for enhanced display in medical education. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:02cc8ccb-33ae-4b07-a402-ac5baf3ec365


University of Waterloo

13. Princz, Daniel. The CRANE Framework for Simulation Model Workflows.

Degree: 2016, University of Waterloo

 CRANE is presented as a flexible framework for linking simulation models and model support tools to form integrated modelling systems for engineering and scientific applications,… (more)

Subjects/Keywords: model calibration; parameter estimation; graphical user interface; simulation model workflow; model-independent software

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

APA (6th Edition):

Princz, D. (2016). The CRANE Framework for Simulation Model Workflows. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/10230

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):

Princz, Daniel. “The CRANE Framework for Simulation Model Workflows.” 2016. Thesis, University of Waterloo. Accessed May 08, 2021. http://hdl.handle.net/10012/10230.

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

MLA Handbook (7th Edition):

Princz, Daniel. “The CRANE Framework for Simulation Model Workflows.” 2016. Web. 08 May 2021.

Vancouver:

Princz D. The CRANE Framework for Simulation Model Workflows. [Internet] [Thesis]. University of Waterloo; 2016. [cited 2021 May 08]. Available from: http://hdl.handle.net/10012/10230.

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

Council of Science Editors:

Princz D. The CRANE Framework for Simulation Model Workflows. [Thesis]. University of Waterloo; 2016. Available from: http://hdl.handle.net/10012/10230

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


Carnegie Mellon University

14. Wytock, Matt. Optimizing Optimization: Scalable Convex Programming with Proximal Operators.

Degree: 2016, Carnegie Mellon University

 Convex optimization has developed a wide variety of useful tools critical to many applications in machine learning. However, unlike linear and quadratic programming, general convex… (more)

Subjects/Keywords: convex optimization; proximal operator; operator splitting; Newton method; sparsity; graphical model

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APA (6th Edition):

Wytock, M. (2016). Optimizing Optimization: Scalable Convex Programming with Proximal Operators. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/785

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):

Wytock, Matt. “Optimizing Optimization: Scalable Convex Programming with Proximal Operators.” 2016. Thesis, Carnegie Mellon University. Accessed May 08, 2021. http://repository.cmu.edu/dissertations/785.

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

MLA Handbook (7th Edition):

Wytock, Matt. “Optimizing Optimization: Scalable Convex Programming with Proximal Operators.” 2016. Web. 08 May 2021.

Vancouver:

Wytock M. Optimizing Optimization: Scalable Convex Programming with Proximal Operators. [Internet] [Thesis]. Carnegie Mellon University; 2016. [cited 2021 May 08]. Available from: http://repository.cmu.edu/dissertations/785.

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

Council of Science Editors:

Wytock M. Optimizing Optimization: Scalable Convex Programming with Proximal Operators. [Thesis]. Carnegie Mellon University; 2016. Available from: http://repository.cmu.edu/dissertations/785

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


University of California – Berkeley

15. Kao, Wei-Chun. Algorithms for Next-Generation High-Throughput Sequencing Technologies.

Degree: Electrical Engineering & Computer Sciences, 2011, University of California – Berkeley

 Recent advances of DNA sequencing technologies are allowingresearchers to generateimmense amounts of data in a fast and cost effective fashion, enablinggenome-wide association study and populationgenetic… (more)

Subjects/Keywords: Computer science; Bioinformatics; Graphical Model; Illumina; Sequencing; Signal processing

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APA (6th Edition):

Kao, W. (2011). Algorithms for Next-Generation High-Throughput Sequencing Technologies. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/86b9c87d

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):

Kao, Wei-Chun. “Algorithms for Next-Generation High-Throughput Sequencing Technologies.” 2011. Thesis, University of California – Berkeley. Accessed May 08, 2021. http://www.escholarship.org/uc/item/86b9c87d.

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

MLA Handbook (7th Edition):

Kao, Wei-Chun. “Algorithms for Next-Generation High-Throughput Sequencing Technologies.” 2011. Web. 08 May 2021.

Vancouver:

Kao W. Algorithms for Next-Generation High-Throughput Sequencing Technologies. [Internet] [Thesis]. University of California – Berkeley; 2011. [cited 2021 May 08]. Available from: http://www.escholarship.org/uc/item/86b9c87d.

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

Council of Science Editors:

Kao W. Algorithms for Next-Generation High-Throughput Sequencing Technologies. [Thesis]. University of California – Berkeley; 2011. Available from: http://www.escholarship.org/uc/item/86b9c87d

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


Mississippi State University

16. Shi, Jinchuan. A framework for integrating influence diagrams and POMDPs.

Degree: PhD, Computer Science and Engineering, 2018, Mississippi State University

 An influence diagram is a widely-used graphical model for representing and solving problems of sequential decision making under imperfect information. A closely-related model for the… (more)

Subjects/Keywords: POMDP; Graphical Model; Probabilistic Inference; Theoretical Decision Planning; Influence Diagram

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

APA (6th Edition):

Shi, J. (2018). A framework for integrating influence diagrams and POMDPs. (Doctoral Dissertation). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-03022018-153923/ ;

Chicago Manual of Style (16th Edition):

Shi, Jinchuan. “A framework for integrating influence diagrams and POMDPs.” 2018. Doctoral Dissertation, Mississippi State University. Accessed May 08, 2021. http://sun.library.msstate.edu/ETD-db/theses/available/etd-03022018-153923/ ;.

MLA Handbook (7th Edition):

Shi, Jinchuan. “A framework for integrating influence diagrams and POMDPs.” 2018. Web. 08 May 2021.

Vancouver:

Shi J. A framework for integrating influence diagrams and POMDPs. [Internet] [Doctoral dissertation]. Mississippi State University; 2018. [cited 2021 May 08]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-03022018-153923/ ;.

Council of Science Editors:

Shi J. A framework for integrating influence diagrams and POMDPs. [Doctoral Dissertation]. Mississippi State University; 2018. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-03022018-153923/ ;


University of Alberta

17. Eastman, Thomas. A disease classifier for metabolic profiles based on metabolic pathway knowledge.

Degree: MS, Department of Computing Science, 2010, University of Alberta

 This thesis presents Pathway Informed Analysis (PIA), a classification method for predicting disease states (diagnosis) from metabolic profile measurements that incorporates biological knowledge in the… (more)

Subjects/Keywords: metabolic profile; cachexia; graphical model; machine learning; metabolic pathway

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

APA (6th Edition):

Eastman, T. (2010). A disease classifier for metabolic profiles based on metabolic pathway knowledge. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/fx719n29m

Chicago Manual of Style (16th Edition):

Eastman, Thomas. “A disease classifier for metabolic profiles based on metabolic pathway knowledge.” 2010. Masters Thesis, University of Alberta. Accessed May 08, 2021. https://era.library.ualberta.ca/files/fx719n29m.

MLA Handbook (7th Edition):

Eastman, Thomas. “A disease classifier for metabolic profiles based on metabolic pathway knowledge.” 2010. Web. 08 May 2021.

Vancouver:

Eastman T. A disease classifier for metabolic profiles based on metabolic pathway knowledge. [Internet] [Masters thesis]. University of Alberta; 2010. [cited 2021 May 08]. Available from: https://era.library.ualberta.ca/files/fx719n29m.

Council of Science Editors:

Eastman T. A disease classifier for metabolic profiles based on metabolic pathway knowledge. [Masters Thesis]. University of Alberta; 2010. Available from: https://era.library.ualberta.ca/files/fx719n29m


University of Alberta

18. Zhu, Yunan. Estimating Sparse Graphical Models: Insights Through Simulation.

Degree: MS, Department of Mathematical and Statistical Sciences, 2015, University of Alberta

Graphical models are frequently used to explore networks among a set of variables. Several methods for estimating sparse graphs have been proposed and their theoretical… (more)

Subjects/Keywords: bootstrap; penalized log-likelihood; graphical model; glasso; estimate evaluation

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

APA (6th Edition):

Zhu, Y. (2015). Estimating Sparse Graphical Models: Insights Through Simulation. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/4j03d241c

Chicago Manual of Style (16th Edition):

Zhu, Yunan. “Estimating Sparse Graphical Models: Insights Through Simulation.” 2015. Masters Thesis, University of Alberta. Accessed May 08, 2021. https://era.library.ualberta.ca/files/4j03d241c.

MLA Handbook (7th Edition):

Zhu, Yunan. “Estimating Sparse Graphical Models: Insights Through Simulation.” 2015. Web. 08 May 2021.

Vancouver:

Zhu Y. Estimating Sparse Graphical Models: Insights Through Simulation. [Internet] [Masters thesis]. University of Alberta; 2015. [cited 2021 May 08]. Available from: https://era.library.ualberta.ca/files/4j03d241c.

Council of Science Editors:

Zhu Y. Estimating Sparse Graphical Models: Insights Through Simulation. [Masters Thesis]. University of Alberta; 2015. Available from: https://era.library.ualberta.ca/files/4j03d241c


Penn State University

19. Agarwal, Amal. Model-Based Clustering of Nonparametric Weighted Networks.

Degree: 2019, Penn State University

 Water pollution is a major global environmental problem, and it poses a great environmental risk to public health and biological diversity. This work is motivated… (more)

Subjects/Keywords: Exponential-family random graphical model; Local likelihood; Variational inference

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APA (6th Edition):

Agarwal, A. (2019). Model-Based Clustering of Nonparametric Weighted Networks. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/17363aua257

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):

Agarwal, Amal. “Model-Based Clustering of Nonparametric Weighted Networks.” 2019. Thesis, Penn State University. Accessed May 08, 2021. https://submit-etda.libraries.psu.edu/catalog/17363aua257.

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

MLA Handbook (7th Edition):

Agarwal, Amal. “Model-Based Clustering of Nonparametric Weighted Networks.” 2019. Web. 08 May 2021.

Vancouver:

Agarwal A. Model-Based Clustering of Nonparametric Weighted Networks. [Internet] [Thesis]. Penn State University; 2019. [cited 2021 May 08]. Available from: https://submit-etda.libraries.psu.edu/catalog/17363aua257.

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

Council of Science Editors:

Agarwal A. Model-Based Clustering of Nonparametric Weighted Networks. [Thesis]. Penn State University; 2019. Available from: https://submit-etda.libraries.psu.edu/catalog/17363aua257

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


University of Toronto

20. Yeo, Alexia. COMBINATORIALLY CONSTRAINED PORTFOLIO OPTIMIZATION USING MESSAGE PASSING ALGORITHMS.

Degree: 2018, University of Toronto

Portfolio optimization aims to find the optimal investment strategy for a series of assets that results in a minimization of the portfolio's variance. Real life… (more)

Subjects/Keywords: Mixed Integer Programming; Portfolio Optimization; Probabilistic Graphical Model; 0796

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

APA (6th Edition):

Yeo, A. (2018). COMBINATORIALLY CONSTRAINED PORTFOLIO OPTIMIZATION USING MESSAGE PASSING ALGORITHMS. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/89580

Chicago Manual of Style (16th Edition):

Yeo, Alexia. “COMBINATORIALLY CONSTRAINED PORTFOLIO OPTIMIZATION USING MESSAGE PASSING ALGORITHMS.” 2018. Masters Thesis, University of Toronto. Accessed May 08, 2021. http://hdl.handle.net/1807/89580.

MLA Handbook (7th Edition):

Yeo, Alexia. “COMBINATORIALLY CONSTRAINED PORTFOLIO OPTIMIZATION USING MESSAGE PASSING ALGORITHMS.” 2018. Web. 08 May 2021.

Vancouver:

Yeo A. COMBINATORIALLY CONSTRAINED PORTFOLIO OPTIMIZATION USING MESSAGE PASSING ALGORITHMS. [Internet] [Masters thesis]. University of Toronto; 2018. [cited 2021 May 08]. Available from: http://hdl.handle.net/1807/89580.

Council of Science Editors:

Yeo A. COMBINATORIALLY CONSTRAINED PORTFOLIO OPTIMIZATION USING MESSAGE PASSING ALGORITHMS. [Masters Thesis]. University of Toronto; 2018. Available from: http://hdl.handle.net/1807/89580


University of Adelaide

21. Wang, Zhenhua. Markov random fields with unknown heterogeneous graphs.

Degree: 2014, University of Adelaide

 Markov Random Fields have been widely used in computer vision problems, for example image denoising, segmentation and human action recognition. The structure of the graph… (more)

Subjects/Keywords: structured learning; Probablistic Graphical Model; Markov Random Field; unknown graph

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

APA (6th Edition):

Wang, Z. (2014). Markov random fields with unknown heterogeneous graphs. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/98246

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):

Wang, Zhenhua. “Markov random fields with unknown heterogeneous graphs.” 2014. Thesis, University of Adelaide. Accessed May 08, 2021. http://hdl.handle.net/2440/98246.

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

MLA Handbook (7th Edition):

Wang, Zhenhua. “Markov random fields with unknown heterogeneous graphs.” 2014. Web. 08 May 2021.

Vancouver:

Wang Z. Markov random fields with unknown heterogeneous graphs. [Internet] [Thesis]. University of Adelaide; 2014. [cited 2021 May 08]. Available from: http://hdl.handle.net/2440/98246.

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

Council of Science Editors:

Wang Z. Markov random fields with unknown heterogeneous graphs. [Thesis]. University of Adelaide; 2014. Available from: http://hdl.handle.net/2440/98246

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


University of Washington

22. Li, Zehang. Bayesian Methods for Graphical Models with Limited Data.

Degree: PhD, 2018, University of Washington

 Scientific studies in many fields involve understanding and characterizing dependence relationships among large numbers of variables. This can be challenging in settings where data is… (more)

Subjects/Keywords: Bayesian methods; Graphical model; Spike-and-slab; Verbal Autopsy; Statistics; Statistics

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

APA (6th Edition):

Li, Z. (2018). Bayesian Methods for Graphical Models with Limited Data. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/43158

Chicago Manual of Style (16th Edition):

Li, Zehang. “Bayesian Methods for Graphical Models with Limited Data.” 2018. Doctoral Dissertation, University of Washington. Accessed May 08, 2021. http://hdl.handle.net/1773/43158.

MLA Handbook (7th Edition):

Li, Zehang. “Bayesian Methods for Graphical Models with Limited Data.” 2018. Web. 08 May 2021.

Vancouver:

Li Z. Bayesian Methods for Graphical Models with Limited Data. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2021 May 08]. Available from: http://hdl.handle.net/1773/43158.

Council of Science Editors:

Li Z. Bayesian Methods for Graphical Models with Limited Data. [Doctoral Dissertation]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/43158


Michigan Technological University

23. Shi, Lufeng. USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS.

Degree: PhD, Department of Electrical and Computer Engineering, 2014, Michigan Technological University

  Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been… (more)

Subjects/Keywords: Graphical Model; Statistical Inference; Target Tracking; Wireless Sensor Network; Computer Engineering

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

APA (6th Edition):

Shi, L. (2014). USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etds/752

Chicago Manual of Style (16th Edition):

Shi, Lufeng. “USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS.” 2014. Doctoral Dissertation, Michigan Technological University. Accessed May 08, 2021. https://digitalcommons.mtu.edu/etds/752.

MLA Handbook (7th Edition):

Shi, Lufeng. “USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS.” 2014. Web. 08 May 2021.

Vancouver:

Shi L. USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS. [Internet] [Doctoral dissertation]. Michigan Technological University; 2014. [cited 2021 May 08]. Available from: https://digitalcommons.mtu.edu/etds/752.

Council of Science Editors:

Shi L. USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS. [Doctoral Dissertation]. Michigan Technological University; 2014. Available from: https://digitalcommons.mtu.edu/etds/752


University of Minnesota

24. Fu, Qiang. Efficient inference algorithms for some probabilistic graphical models.

Degree: PhD, Computer science, 2014, University of Minnesota

 The probabilistic graphical model framework provides an essential tool to reason coherently from limited and noisy observations. The framework has been used in an enormous… (more)

Subjects/Keywords: Bayesian network; Graphical model; MAP inference; Markov random field; Overlapping; Clustering

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

APA (6th Edition):

Fu, Q. (2014). Efficient inference algorithms for some probabilistic graphical models. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/162960

Chicago Manual of Style (16th Edition):

Fu, Qiang. “Efficient inference algorithms for some probabilistic graphical models.” 2014. Doctoral Dissertation, University of Minnesota. Accessed May 08, 2021. http://hdl.handle.net/11299/162960.

MLA Handbook (7th Edition):

Fu, Qiang. “Efficient inference algorithms for some probabilistic graphical models.” 2014. Web. 08 May 2021.

Vancouver:

Fu Q. Efficient inference algorithms for some probabilistic graphical models. [Internet] [Doctoral dissertation]. University of Minnesota; 2014. [cited 2021 May 08]. Available from: http://hdl.handle.net/11299/162960.

Council of Science Editors:

Fu Q. Efficient inference algorithms for some probabilistic graphical models. [Doctoral Dissertation]. University of Minnesota; 2014. Available from: http://hdl.handle.net/11299/162960


University of Georgia

25. Sulek, Thaddeus Robert. An application of graphical models to fMRI data using the lasso penalty.

Degree: 2018, University of Georgia

 In this thesis, we study the graphical lasso method and apply it to functional magnetic resonance imaging (fMRI) data. The graphical lasso method enables one… (more)

Subjects/Keywords: Functional Magnetic Resonance Imaging Data; Graphical Model; Lasso; Regions of Interest

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

APA (6th Edition):

Sulek, T. R. (2018). An application of graphical models to fMRI data using the lasso penalty. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/37031

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):

Sulek, Thaddeus Robert. “An application of graphical models to fMRI data using the lasso penalty.” 2018. Thesis, University of Georgia. Accessed May 08, 2021. http://hdl.handle.net/10724/37031.

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

MLA Handbook (7th Edition):

Sulek, Thaddeus Robert. “An application of graphical models to fMRI data using the lasso penalty.” 2018. Web. 08 May 2021.

Vancouver:

Sulek TR. An application of graphical models to fMRI data using the lasso penalty. [Internet] [Thesis]. University of Georgia; 2018. [cited 2021 May 08]. Available from: http://hdl.handle.net/10724/37031.

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

Council of Science Editors:

Sulek TR. An application of graphical models to fMRI data using the lasso penalty. [Thesis]. University of Georgia; 2018. Available from: http://hdl.handle.net/10724/37031

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


University of Georgia

26. Sulek, Thaddeus Robert. An application of graphical models to fMRI data using the lasso penalty.

Degree: 2018, University of Georgia

 In this thesis, we study the graphical lasso method and apply it to functional magnetic resonance imaging (fMRI) data. The graphical lasso method enables one… (more)

Subjects/Keywords: Functional Magnetic Resonance Imaging Data; Graphical Model; Lasso; Regions of Interest

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

APA (6th Edition):

Sulek, T. R. (2018). An application of graphical models to fMRI data using the lasso penalty. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/37188

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):

Sulek, Thaddeus Robert. “An application of graphical models to fMRI data using the lasso penalty.” 2018. Thesis, University of Georgia. Accessed May 08, 2021. http://hdl.handle.net/10724/37188.

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

MLA Handbook (7th Edition):

Sulek, Thaddeus Robert. “An application of graphical models to fMRI data using the lasso penalty.” 2018. Web. 08 May 2021.

Vancouver:

Sulek TR. An application of graphical models to fMRI data using the lasso penalty. [Internet] [Thesis]. University of Georgia; 2018. [cited 2021 May 08]. Available from: http://hdl.handle.net/10724/37188.

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

Council of Science Editors:

Sulek TR. An application of graphical models to fMRI data using the lasso penalty. [Thesis]. University of Georgia; 2018. Available from: http://hdl.handle.net/10724/37188

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


University of Cambridge

27. Pacini, Clare. Inferring condition specific regulatory networks with small sample sizes : a case study in Bacillus subtilis and infection of Mus musculus by the parasite Toxoplasma gondii.

Degree: PhD, 2017, University of Cambridge

 Modelling interactions between genes and their regulators is fundamental to understanding how, for example a disease progresses, or the impact of inserting a synthetic circuit… (more)

Subjects/Keywords: 572.8; Gaussian graphical model; Regulatory network; Small sample sizes

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APA (6th Edition):

Pacini, C. (2017). Inferring condition specific regulatory networks with small sample sizes : a case study in Bacillus subtilis and infection of Mus musculus by the parasite Toxoplasma gondii. (Doctoral Dissertation). University of Cambridge. Retrieved from https://doi.org/10.17863/CAM.16660 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744325

Chicago Manual of Style (16th Edition):

Pacini, Clare. “Inferring condition specific regulatory networks with small sample sizes : a case study in Bacillus subtilis and infection of Mus musculus by the parasite Toxoplasma gondii.” 2017. Doctoral Dissertation, University of Cambridge. Accessed May 08, 2021. https://doi.org/10.17863/CAM.16660 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744325.

MLA Handbook (7th Edition):

Pacini, Clare. “Inferring condition specific regulatory networks with small sample sizes : a case study in Bacillus subtilis and infection of Mus musculus by the parasite Toxoplasma gondii.” 2017. Web. 08 May 2021.

Vancouver:

Pacini C. Inferring condition specific regulatory networks with small sample sizes : a case study in Bacillus subtilis and infection of Mus musculus by the parasite Toxoplasma gondii. [Internet] [Doctoral dissertation]. University of Cambridge; 2017. [cited 2021 May 08]. Available from: https://doi.org/10.17863/CAM.16660 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744325.

Council of Science Editors:

Pacini C. Inferring condition specific regulatory networks with small sample sizes : a case study in Bacillus subtilis and infection of Mus musculus by the parasite Toxoplasma gondii. [Doctoral Dissertation]. University of Cambridge; 2017. Available from: https://doi.org/10.17863/CAM.16660 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744325


Virginia Tech

28. Wang, Yizhi. Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data.

Degree: PhD, Electrical Engineering, 2019, Virginia Tech

 Astrocyte is an important type of glial cell in the brain. Unlike neurons, astrocyte cannot be electrically excited. However, the concentrations of many different molecules… (more)

Subjects/Keywords: Astrocyte activity; Image analysis; Curve alignment; Graphical model

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APA (6th Edition):

Wang, Y. (2019). Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/95988

Chicago Manual of Style (16th Edition):

Wang, Yizhi. “Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data.” 2019. Doctoral Dissertation, Virginia Tech. Accessed May 08, 2021. http://hdl.handle.net/10919/95988.

MLA Handbook (7th Edition):

Wang, Yizhi. “Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data.” 2019. Web. 08 May 2021.

Vancouver:

Wang Y. Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 May 08]. Available from: http://hdl.handle.net/10919/95988.

Council of Science Editors:

Wang Y. Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/95988

29. Lin, Jiali. Bayesian Multilevel-multiclass Graphical Model.

Degree: PhD, Statistics, 2019, Virginia Tech

 Gaussian graphical model has been a popular tool to investigate conditional dependency between random variables by estimating sparse precision matrices. Two problems have been discussed.… (more)

Subjects/Keywords: Gaussian graphical model

…Directed acyclic graphical model representing the Bayesian mixture of Gaussians model, Only the X… …graphical model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 2.12 Estimated… …by using Gaussian graphical model with fixed threshold t of 0.6 on 100 simulated PM runs… …otherwise, they are dependent given all other genes. Gaussian graphical model has been widely… …Learning the graph topology via Gaussian graphical model (GGMs) is equivalent to… 

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

APA (6th Edition):

Lin, J. (2019). Bayesian Multilevel-multiclass Graphical Model. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/101092

Chicago Manual of Style (16th Edition):

Lin, Jiali. “Bayesian Multilevel-multiclass Graphical Model.” 2019. Doctoral Dissertation, Virginia Tech. Accessed May 08, 2021. http://hdl.handle.net/10919/101092.

MLA Handbook (7th Edition):

Lin, Jiali. “Bayesian Multilevel-multiclass Graphical Model.” 2019. Web. 08 May 2021.

Vancouver:

Lin J. Bayesian Multilevel-multiclass Graphical Model. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 May 08]. Available from: http://hdl.handle.net/10919/101092.

Council of Science Editors:

Lin J. Bayesian Multilevel-multiclass Graphical Model. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/101092

30. Pacini, Clare. Inferring condition specific regulatory networks with small sample sizes: a case study in bacillus subtilis and infection of mus musculus by the parasite Toxoplasma gondii.

Degree: PhD, 2017, University of Cambridge

 Modelling interactions between genes and their regulators is fundamental to understanding how, for example a disease progresses, or the impact of inserting a synthetic circuit… (more)

Subjects/Keywords: Gaussian graphical model; Regulatory network; Small sample sizes

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

APA (6th Edition):

Pacini, C. (2017). Inferring condition specific regulatory networks with small sample sizes: a case study in bacillus subtilis and infection of mus musculus by the parasite Toxoplasma gondii. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/269711https://www.repository.cam.ac.uk/bitstream/1810/269711/2/694b7167-f7fd-4be5-819f-a1d52c7041be_confirmations.txt ; https://www.repository.cam.ac.uk/bitstream/1810/269711/3/license.txt ; https://www.repository.cam.ac.uk/bitstream/1810/269711/4/694b7167-f7fd-4be5-819f-a1d52c7041be.zip ; https://www.repository.cam.ac.uk/bitstream/1810/269711/5/Pacini-2017-PhD.pdf.txt ; https://www.repository.cam.ac.uk/bitstream/1810/269711/6/Pacini-2017-PhD.pdf.jpg

Chicago Manual of Style (16th Edition):

Pacini, Clare. “Inferring condition specific regulatory networks with small sample sizes: a case study in bacillus subtilis and infection of mus musculus by the parasite Toxoplasma gondii.” 2017. Doctoral Dissertation, University of Cambridge. Accessed May 08, 2021. https://www.repository.cam.ac.uk/handle/1810/269711https://www.repository.cam.ac.uk/bitstream/1810/269711/2/694b7167-f7fd-4be5-819f-a1d52c7041be_confirmations.txt ; https://www.repository.cam.ac.uk/bitstream/1810/269711/3/license.txt ; https://www.repository.cam.ac.uk/bitstream/1810/269711/4/694b7167-f7fd-4be5-819f-a1d52c7041be.zip ; https://www.repository.cam.ac.uk/bitstream/1810/269711/5/Pacini-2017-PhD.pdf.txt ; https://www.repository.cam.ac.uk/bitstream/1810/269711/6/Pacini-2017-PhD.pdf.jpg.

MLA Handbook (7th Edition):

Pacini, Clare. “Inferring condition specific regulatory networks with small sample sizes: a case study in bacillus subtilis and infection of mus musculus by the parasite Toxoplasma gondii.” 2017. Web. 08 May 2021.

Vancouver:

Pacini C. Inferring condition specific regulatory networks with small sample sizes: a case study in bacillus subtilis and infection of mus musculus by the parasite Toxoplasma gondii. [Internet] [Doctoral dissertation]. University of Cambridge; 2017. [cited 2021 May 08]. Available from: https://www.repository.cam.ac.uk/handle/1810/269711https://www.repository.cam.ac.uk/bitstream/1810/269711/2/694b7167-f7fd-4be5-819f-a1d52c7041be_confirmations.txt ; https://www.repository.cam.ac.uk/bitstream/1810/269711/3/license.txt ; https://www.repository.cam.ac.uk/bitstream/1810/269711/4/694b7167-f7fd-4be5-819f-a1d52c7041be.zip ; https://www.repository.cam.ac.uk/bitstream/1810/269711/5/Pacini-2017-PhD.pdf.txt ; https://www.repository.cam.ac.uk/bitstream/1810/269711/6/Pacini-2017-PhD.pdf.jpg.

Council of Science Editors:

Pacini C. Inferring condition specific regulatory networks with small sample sizes: a case study in bacillus subtilis and infection of mus musculus by the parasite Toxoplasma gondii. [Doctoral Dissertation]. University of Cambridge; 2017. Available from: https://www.repository.cam.ac.uk/handle/1810/269711https://www.repository.cam.ac.uk/bitstream/1810/269711/2/694b7167-f7fd-4be5-819f-a1d52c7041be_confirmations.txt ; https://www.repository.cam.ac.uk/bitstream/1810/269711/3/license.txt ; https://www.repository.cam.ac.uk/bitstream/1810/269711/4/694b7167-f7fd-4be5-819f-a1d52c7041be.zip ; https://www.repository.cam.ac.uk/bitstream/1810/269711/5/Pacini-2017-PhD.pdf.txt ; https://www.repository.cam.ac.uk/bitstream/1810/269711/6/Pacini-2017-PhD.pdf.jpg

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