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167 total matches.

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- 2012 – 2016 (77)
- 2007 – 2011 (23)
- 2002 – 2006 (11)

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- Computer Science (14)
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Virginia Tech

1.
Lin, Jiali.
Bayesian Multilevel-multiclass *Graphical* * Model*.

Degree: PhD, Statistics, 2019, Virginia Tech

URL: http://hdl.handle.net/10919/101092

► 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

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

APA (6^{th} 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 (16^{th} Edition):

Lin, Jiali. “Bayesian Multilevel-multiclass Graphical Model.” 2019. Doctoral Dissertation, Virginia Tech. Accessed January 16, 2021. http://hdl.handle.net/10919/101092.

MLA Handbook (7^{th} Edition):

Lin, Jiali. “Bayesian Multilevel-multiclass Graphical Model.” 2019. Web. 16 Jan 2021.

Vancouver:

Lin J. Bayesian Multilevel-multiclass Graphical Model. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 Jan 16]. 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

University of Alberta

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

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

URL: https://era.library.ualberta.ca/files/pv63g128r

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

APA (6^{th} 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 (16^{th} Edition):

Sen, Abhishek. “Hand Tracking by Fusion of Color and a Range Sensor.” 2012. Masters Thesis, University of Alberta. Accessed January 16, 2021. https://era.library.ualberta.ca/files/pv63g128r.

MLA Handbook (7^{th} Edition):

Sen, Abhishek. “Hand Tracking by Fusion of Color and a Range Sensor.” 2012. Web. 16 Jan 2021.

Vancouver:

Sen A. Hand Tracking by Fusion of Color and a Range Sensor. [Internet] [Masters thesis]. University of Alberta; 2012. [cited 2021 Jan 16]. 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

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

Degree: PhD, 2011, University of Rochester

URL: http://hdl.handle.net/1802/15981

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

APA (6^{th} 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 (16^{th} Edition):

LaCombe, Jason R. “Non-Informative Priors for Structural Inference in Bayesian Networks.” 2011. Doctoral Dissertation, University of Rochester. Accessed January 16, 2021. http://hdl.handle.net/1802/15981.

MLA Handbook (7^{th} Edition):

LaCombe, Jason R. “Non-Informative Priors for Structural Inference in Bayesian Networks.” 2011. Web. 16 Jan 2021.

Vancouver:

LaCombe JR. Non-Informative Priors for Structural Inference in Bayesian Networks. [Internet] [Doctoral dissertation]. University of Rochester; 2011. [cited 2021 Jan 16]. 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

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

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

URL: http://hdl.handle.net/2144/33117

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

APA (6^{th} 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 (16^{th} Edition):

Kang, Xinyu. “Statistical methods for topology inference, denoising, and bootstrapping in networks.” 2018. Doctoral Dissertation, Boston University. Accessed January 16, 2021. http://hdl.handle.net/2144/33117.

MLA Handbook (7^{th} Edition):

Kang, Xinyu. “Statistical methods for topology inference, denoising, and bootstrapping in networks.” 2018. Web. 16 Jan 2021.

Vancouver:

Kang X. Statistical methods for topology inference, denoising, and bootstrapping in networks. [Internet] [Doctoral dissertation]. Boston University; 2018. [cited 2021 Jan 16]. 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

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

Degree: 2012, University of Missouri – Columbia

URL: http://hdl.handle.net/10355/15884

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

APA (6^{th} 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 (16^{th} Edition):

Liang, Ye. “Bayesian methods on selected topics.” 2012. Thesis, University of Missouri – Columbia. Accessed January 16, 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 (7^{th} Edition):

Liang, Ye. “Bayesian methods on selected topics.” 2012. Web. 16 Jan 2021.

Vancouver:

Liang Y. Bayesian methods on selected topics. [Internet] [Thesis]. University of Missouri – Columbia; 2012. [cited 2021 Jan 16]. 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

Not specified: Masters Thesis or Doctoral Dissertation

University of New South Wales

6.
Liu, Xianghang.
New Algorithms for *Graphical* Models and Their Applications in Learning.

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

URL: http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Liu, Xianghang. “New Algorithms for Graphical Models and Their Applications in Learning.” 2015. Doctoral Dissertation, University of New South Wales. Accessed January 16, 2021. http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true.

MLA Handbook (7^{th} Edition):

Liu, Xianghang. “New Algorithms for Graphical Models and Their Applications in Learning.” 2015. Web. 16 Jan 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 Jan 16]. 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

7.
Zhang, Yafei.
Variable screening and *graphical* modeling for ultra-high dimensional longitudinal data.

Degree: PhD, Statistics, 2019, Virginia Tech

URL: http://hdl.handle.net/10919/101662

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Zhang, Yafei. “Variable screening and graphical modeling for ultra-high dimensional longitudinal data.” 2019. Doctoral Dissertation, Virginia Tech. Accessed January 16, 2021. http://hdl.handle.net/10919/101662.

MLA Handbook (7^{th} Edition):

Zhang, Yafei. “Variable screening and graphical modeling for ultra-high dimensional longitudinal data.” 2019. Web. 16 Jan 2021.

Vancouver:

Zhang Y. Variable screening and graphical modeling for ultra-high dimensional longitudinal data. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 Jan 16]. 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

University of California – Irvine

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

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

URL: http://www.escholarship.org/uc/item/7q90z4b5

► 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

Record Details Similar Records

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Ping, Wei. “Learning and Inference in Latent Variable Graphical Models.” 2016. Thesis, University of California – Irvine. Accessed January 16, 2021. http://www.escholarship.org/uc/item/7q90z4b5.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Ping, Wei. “Learning and Inference in Latent Variable Graphical Models.” 2016. Web. 16 Jan 2021.

Vancouver:

Ping W. Learning and Inference in Latent Variable Graphical Models. [Internet] [Thesis]. University of California – Irvine; 2016. [cited 2021 Jan 16]. Available from: http://www.escholarship.org/uc/item/7q90z4b5.

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

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

URL: https://submit-etda.libraries.psu.edu/catalog/14976sxl439

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Lee, Sanghack. “Causal Discovery from Relational Data: Theory and Practice.” 2018. Thesis, Penn State University. Accessed January 16, 2021. https://submit-etda.libraries.psu.edu/catalog/14976sxl439.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Lee, Sanghack. “Causal Discovery from Relational Data: Theory and Practice.” 2018. Web. 16 Jan 2021.

Vancouver:

Lee S. Causal Discovery from Relational Data: Theory and Practice. [Internet] [Thesis]. Penn State University; 2018. [cited 2021 Jan 16]. Available from: https://submit-etda.libraries.psu.edu/catalog/14976sxl439.

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

Not specified: Masters Thesis or Doctoral Dissertation

University of Waterloo

10.
Princz, Daniel.
The CRANE Framework for Simulation *Model* Workflows.

Degree: 2016, University of Waterloo

URL: http://hdl.handle.net/10012/10230

► 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

Record Details Similar Records

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

APA (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Princz, Daniel. “The CRANE Framework for Simulation Model Workflows.” 2016. Thesis, University of Waterloo. Accessed January 16, 2021. http://hdl.handle.net/10012/10230.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Princz, Daniel. “The CRANE Framework for Simulation Model Workflows.” 2016. Web. 16 Jan 2021.

Vancouver:

Princz D. The CRANE Framework for Simulation Model Workflows. [Internet] [Thesis]. University of Waterloo; 2016. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/10012/10230.

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

Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

11.
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

URL: http://resolver.tudelft.nl/uuid:02cc8ccb-33ae-4b07-a402-ac5baf3ec365

►

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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} 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 January 16, 2021. http://resolver.tudelft.nl/uuid:02cc8ccb-33ae-4b07-a402-ac5baf3ec365.

MLA Handbook (7^{th} 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. 16 Jan 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 Jan 16]. 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

Carnegie Mellon University

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

Degree: 2016, Carnegie Mellon University

URL: http://repository.cmu.edu/dissertations/785

► 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

Record Details Similar Records

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

APA (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Wytock, Matt. “Optimizing Optimization: Scalable Convex Programming with Proximal Operators.” 2016. Thesis, Carnegie Mellon University. Accessed January 16, 2021. http://repository.cmu.edu/dissertations/785.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Wytock, Matt. “Optimizing Optimization: Scalable Convex Programming with Proximal Operators.” 2016. Web. 16 Jan 2021.

Vancouver:

Wytock M. Optimizing Optimization: Scalable Convex Programming with Proximal Operators. [Internet] [Thesis]. Carnegie Mellon University; 2016. [cited 2021 Jan 16]. Available from: http://repository.cmu.edu/dissertations/785.

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

Not specified: Masters Thesis or Doctoral Dissertation

University of California – Berkeley

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

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

URL: http://www.escholarship.org/uc/item/86b9c87d

► 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

Record Details Similar Records

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Kao, Wei-Chun. “Algorithms for Next-Generation High-Throughput Sequencing Technologies.” 2011. Thesis, University of California – Berkeley. Accessed January 16, 2021. http://www.escholarship.org/uc/item/86b9c87d.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Kao, Wei-Chun. “Algorithms for Next-Generation High-Throughput Sequencing Technologies.” 2011. Web. 16 Jan 2021.

Vancouver:

Kao W. Algorithms for Next-Generation High-Throughput Sequencing Technologies. [Internet] [Thesis]. University of California – Berkeley; 2011. [cited 2021 Jan 16]. Available from: http://www.escholarship.org/uc/item/86b9c87d.

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

Not specified: Masters Thesis or Doctoral Dissertation

Mississippi State University

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

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

URL: http://sun.library.msstate.edu/ETD-db/theses/available/etd-03022018-153923/ ;

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Shi, Jinchuan. “A framework for integrating influence diagrams and POMDPs.” 2018. Doctoral Dissertation, Mississippi State University. Accessed January 16, 2021. http://sun.library.msstate.edu/ETD-db/theses/available/etd-03022018-153923/ ;.

MLA Handbook (7^{th} Edition):

Shi, Jinchuan. “A framework for integrating influence diagrams and POMDPs.” 2018. Web. 16 Jan 2021.

Vancouver:

Shi J. A framework for integrating influence diagrams and POMDPs. [Internet] [Doctoral dissertation]. Mississippi State University; 2018. [cited 2021 Jan 16]. 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

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

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

URL: https://era.library.ualberta.ca/files/fx719n29m

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Eastman, Thomas. “A disease classifier for metabolic profiles based on metabolic pathway knowledge.” 2010. Masters Thesis, University of Alberta. Accessed January 16, 2021. https://era.library.ualberta.ca/files/fx719n29m.

MLA Handbook (7^{th} Edition):

Eastman, Thomas. “A disease classifier for metabolic profiles based on metabolic pathway knowledge.” 2010. Web. 16 Jan 2021.

Vancouver:

Eastman T. A disease classifier for metabolic profiles based on metabolic pathway knowledge. [Internet] [Masters thesis]. University of Alberta; 2010. [cited 2021 Jan 16]. 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

16.
Zhu, Yunan.
Estimating Sparse *Graphical* Models: Insights Through
Simulation.

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

URL: https://era.library.ualberta.ca/files/4j03d241c

► *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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Zhu, Yunan. “Estimating Sparse Graphical Models: Insights Through Simulation.” 2015. Masters Thesis, University of Alberta. Accessed January 16, 2021. https://era.library.ualberta.ca/files/4j03d241c.

MLA Handbook (7^{th} Edition):

Zhu, Yunan. “Estimating Sparse Graphical Models: Insights Through Simulation.” 2015. Web. 16 Jan 2021.

Vancouver:

Zhu Y. Estimating Sparse Graphical Models: Insights Through Simulation. [Internet] [Masters thesis]. University of Alberta; 2015. [cited 2021 Jan 16]. 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

17.
Agarwal, Amal.
* Model*-Based Clustering of Nonparametric Weighted Networks.

Degree: 2019, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/17363aua257

► 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

Record Details Similar Records

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Agarwal, Amal. “Model-Based Clustering of Nonparametric Weighted Networks.” 2019. Thesis, Penn State University. Accessed January 16, 2021. https://submit-etda.libraries.psu.edu/catalog/17363aua257.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Agarwal, Amal. “Model-Based Clustering of Nonparametric Weighted Networks.” 2019. Web. 16 Jan 2021.

Vancouver:

Agarwal A. Model-Based Clustering of Nonparametric Weighted Networks. [Internet] [Thesis]. Penn State University; 2019. [cited 2021 Jan 16]. Available from: https://submit-etda.libraries.psu.edu/catalog/17363aua257.

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

Not specified: Masters Thesis or Doctoral Dissertation

University of Toronto

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

Degree: 2018, University of Toronto

URL: http://hdl.handle.net/1807/89580

►

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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Yeo, Alexia. “COMBINATORIALLY CONSTRAINED PORTFOLIO OPTIMIZATION USING MESSAGE PASSING ALGORITHMS.” 2018. Masters Thesis, University of Toronto. Accessed January 16, 2021. http://hdl.handle.net/1807/89580.

MLA Handbook (7^{th} Edition):

Yeo, Alexia. “COMBINATORIALLY CONSTRAINED PORTFOLIO OPTIMIZATION USING MESSAGE PASSING ALGORITHMS.” 2018. Web. 16 Jan 2021.

Vancouver:

Yeo A. COMBINATORIALLY CONSTRAINED PORTFOLIO OPTIMIZATION USING MESSAGE PASSING ALGORITHMS. [Internet] [Masters thesis]. University of Toronto; 2018. [cited 2021 Jan 16]. 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

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

Degree: 2014, University of Adelaide

URL: http://hdl.handle.net/2440/98246

► 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

Record Details Similar Records

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

APA (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Wang, Zhenhua. “Markov random fields with unknown heterogeneous graphs.” 2014. Thesis, University of Adelaide. Accessed January 16, 2021. http://hdl.handle.net/2440/98246.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Wang, Zhenhua. “Markov random fields with unknown heterogeneous graphs.” 2014. Web. 16 Jan 2021.

Vancouver:

Wang Z. Markov random fields with unknown heterogeneous graphs. [Internet] [Thesis]. University of Adelaide; 2014. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/2440/98246.

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

Not specified: Masters Thesis or Doctoral Dissertation

20. 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

URL: https://www.repository.cam.ac.uk/handle/1810/269711

► 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

Record Details Similar Records

❌

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

APA (6^{th} 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/1810/269711

Chicago Manual of Style (16^{th} 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 January 16, 2021. https://www.repository.cam.ac.uk/handle/1810/269711.

MLA Handbook (7^{th} 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. 16 Jan 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 Jan 16]. Available from: https://www.repository.cam.ac.uk/handle/1810/269711.

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/1810/269711

University of Washington

21.
Li, Zehang.
Bayesian Methods for *Graphical* Models with Limited Data.

Degree: PhD, 2018, University of Washington

URL: http://hdl.handle.net/1773/43158

► 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

Record Details Similar Records

❌

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

APA (6^{th} 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 (16^{th} Edition):

Li, Zehang. “Bayesian Methods for Graphical Models with Limited Data.” 2018. Doctoral Dissertation, University of Washington. Accessed January 16, 2021. http://hdl.handle.net/1773/43158.

MLA Handbook (7^{th} Edition):

Li, Zehang. “Bayesian Methods for Graphical Models with Limited Data.” 2018. Web. 16 Jan 2021.

Vancouver:

Li Z. Bayesian Methods for Graphical Models with Limited Data. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2021 Jan 16]. 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

22.
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

URL: https://digitalcommons.mtu.edu/etds/752

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Shi, Lufeng. “USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS.” 2014. Doctoral Dissertation, Michigan Technological University. Accessed January 16, 2021. https://digitalcommons.mtu.edu/etds/752.

MLA Handbook (7^{th} Edition):

Shi, Lufeng. “USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS.” 2014. Web. 16 Jan 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 Jan 16]. 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

23.
Fu, Qiang.
Efficient inference algorithms for some probabilistic *graphical* models.

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

URL: http://hdl.handle.net/11299/162960

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Fu, Qiang. “Efficient inference algorithms for some probabilistic graphical models.” 2014. Doctoral Dissertation, University of Minnesota. Accessed January 16, 2021. http://hdl.handle.net/11299/162960.

MLA Handbook (7^{th} Edition):

Fu, Qiang. “Efficient inference algorithms for some probabilistic graphical models.” 2014. Web. 16 Jan 2021.

Vancouver:

Fu Q. Efficient inference algorithms for some probabilistic graphical models. [Internet] [Doctoral dissertation]. University of Minnesota; 2014. [cited 2021 Jan 16]. 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

24.
Sulek, Thaddeus Robert.
An application of *graphical* models to fMRI data using the lasso penalty.

Degree: 2018, University of Georgia

URL: http://hdl.handle.net/10724/37031

► 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

Record Details Similar Records

❌

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Sulek, Thaddeus Robert. “An application of graphical models to fMRI data using the lasso penalty.” 2018. Thesis, University of Georgia. Accessed January 16, 2021. http://hdl.handle.net/10724/37031.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Sulek, Thaddeus Robert. “An application of graphical models to fMRI data using the lasso penalty.” 2018. Web. 16 Jan 2021.

Vancouver:

Sulek TR. An application of graphical models to fMRI data using the lasso penalty. [Internet] [Thesis]. University of Georgia; 2018. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/10724/37031.

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

Not specified: Masters Thesis or Doctoral Dissertation

University of Georgia

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

Degree: 2018, University of Georgia

URL: http://hdl.handle.net/10724/37188

► 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

Record Details Similar Records

❌

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Sulek, Thaddeus Robert. “An application of graphical models to fMRI data using the lasso penalty.” 2018. Thesis, University of Georgia. Accessed January 16, 2021. http://hdl.handle.net/10724/37188.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Sulek, Thaddeus Robert. “An application of graphical models to fMRI data using the lasso penalty.” 2018. Web. 16 Jan 2021.

Vancouver:

Sulek TR. An application of graphical models to fMRI data using the lasso penalty. [Internet] [Thesis]. University of Georgia; 2018. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/10724/37188.

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

Not specified: Masters Thesis or Doctoral Dissertation

University of Cambridge

26. 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

URL: https://doi.org/10.17863/CAM.16660 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744325

► 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

Record Details Similar Records

❌

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

APA (6^{th} 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 (16^{th} 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 January 16, 2021. https://doi.org/10.17863/CAM.16660 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744325.

MLA Handbook (7^{th} 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. 16 Jan 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 Jan 16]. 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

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

Degree: PhD, Electrical Engineering, 2019, Virginia Tech

URL: http://hdl.handle.net/10919/95988

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} Edition):

Wang, Yizhi. “Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data.” 2019. Doctoral Dissertation, Virginia Tech. Accessed January 16, 2021. http://hdl.handle.net/10919/95988.

MLA Handbook (7^{th} Edition):

Wang, Yizhi. “Automated Analysis of Astrocyte Activities from Large-scale Time-lapse Microscopic Imaging Data.” 2019. Web. 16 Jan 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 Jan 16]. 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

Virginia Tech

28.
Shan, Liang.
Joint Gaussian *Graphical* *Model* for multi-class and multi-level data.

Degree: PhD, Statistics, 2016, Virginia Tech

URL: http://hdl.handle.net/10919/81412

► Gaussian *graphical* *model* has been a popular tool to investigate conditional dependency between random variables by estimating sparse precision matrices. The estimated precision matrices could…
(more)

Subjects/Keywords: Bias Correction; Gaussian graphical model; Heterogeneous classes; Joint adaptive graphical lasso; Joint estimation; Multilevel network; Precision matrix; Unbalanced multi-class.

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Shan, L. (2016). Joint Gaussian Graphical Model for multi-class and multi-level data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/81412

Chicago Manual of Style (16^{th} Edition):

Shan, Liang. “Joint Gaussian Graphical Model for multi-class and multi-level data.” 2016. Doctoral Dissertation, Virginia Tech. Accessed January 16, 2021. http://hdl.handle.net/10919/81412.

MLA Handbook (7^{th} Edition):

Shan, Liang. “Joint Gaussian Graphical Model for multi-class and multi-level data.” 2016. Web. 16 Jan 2021.

Vancouver:

Shan L. Joint Gaussian Graphical Model for multi-class and multi-level data. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/10919/81412.

Council of Science Editors:

Shan L. Joint Gaussian Graphical Model for multi-class and multi-level data. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/81412

Penn State University

29. Lee, Kevin Haeseung. Statistical Learning of Complex Large-Scale Dynamic Systems.

Degree: 2017, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/14151khl119

► Due to advances in data collection technologies, large-scale network/graph analysis has been increasingly important in various research fields such as artificial intelligence, business, finance, genomics,…
(more)

Subjects/Keywords: Statistical learning; Model-based clustering; Dynamic networks; Graphical model; EM algorithm; Variational inference

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Lee, K. H. (2017). Statistical Learning of Complex Large-Scale Dynamic Systems. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/14151khl119

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Lee, Kevin Haeseung. “Statistical Learning of Complex Large-Scale Dynamic Systems.” 2017. Thesis, Penn State University. Accessed January 16, 2021. https://submit-etda.libraries.psu.edu/catalog/14151khl119.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Lee, Kevin Haeseung. “Statistical Learning of Complex Large-Scale Dynamic Systems.” 2017. Web. 16 Jan 2021.

Vancouver:

Lee KH. Statistical Learning of Complex Large-Scale Dynamic Systems. [Internet] [Thesis]. Penn State University; 2017. [cited 2021 Jan 16]. Available from: https://submit-etda.libraries.psu.edu/catalog/14151khl119.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lee KH. Statistical Learning of Complex Large-Scale Dynamic Systems. [Thesis]. Penn State University; 2017. Available from: https://submit-etda.libraries.psu.edu/catalog/14151khl119

Not specified: Masters Thesis or Doctoral Dissertation

Brno University of Technology

30. Hraboš, Martin. Simulátor robotického pracoviště: Simulator of Robotic Arm Workcell.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/54934

► This thesis describes design and implementation of an application for simulating robotic arm. The real *model* of this robot is located in the Faculty of…
(more)

Subjects/Keywords: simulace; robotika; model; grafické rozhraní; OpenRAVE; Qt; simulation; robotics; model; graphical interface; OpenRAVE; Qt

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Hraboš, M. (2019). Simulátor robotického pracoviště: Simulator of Robotic Arm Workcell. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/54934

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Hraboš, Martin. “Simulátor robotického pracoviště: Simulator of Robotic Arm Workcell.” 2019. Thesis, Brno University of Technology. Accessed January 16, 2021. http://hdl.handle.net/11012/54934.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Hraboš, Martin. “Simulátor robotického pracoviště: Simulator of Robotic Arm Workcell.” 2019. Web. 16 Jan 2021.

Vancouver:

Hraboš M. Simulátor robotického pracoviště: Simulator of Robotic Arm Workcell. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/11012/54934.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hraboš M. Simulátor robotického pracoviště: Simulator of Robotic Arm Workcell. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/54934

Not specified: Masters Thesis or Doctoral Dissertation