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You searched for +publisher:"Brown University" +contributor:("Sudderth, Erik"). Showing records 1 – 16 of 16 total matches.

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1. Sun, Deqing. From Pixels to Layers: Joint Motion Estimation and Segmentation.

Degree: PhD, Computer Science, 2013, Brown University

 Estimating image motion, or optical flow, in scenes with multiple moving objects and segmenting the individual moving objects are two fundamental problems in computer vision… (more)

Subjects/Keywords: optical flow

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APA (6th Edition):

Sun, D. (2013). From Pixels to Layers: Joint Motion Estimation and Segmentation. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:320469/

Chicago Manual of Style (16th Edition):

Sun, Deqing. “From Pixels to Layers: Joint Motion Estimation and Segmentation.” 2013. Doctoral Dissertation, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:320469/.

MLA Handbook (7th Edition):

Sun, Deqing. “From Pixels to Layers: Joint Motion Estimation and Segmentation.” 2013. Web. 15 Sep 2019.

Vancouver:

Sun D. From Pixels to Layers: Joint Motion Estimation and Segmentation. [Internet] [Doctoral dissertation]. Brown University; 2013. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:320469/.

Council of Science Editors:

Sun D. From Pixels to Layers: Joint Motion Estimation and Segmentation. [Doctoral Dissertation]. Brown University; 2013. Available from: https://repository.library.brown.edu/studio/item/bdr:320469/

2. Zuffi, Silvia. Shape Models of the Human Body for Distributed Inference.

Degree: PhD, Computer Science, 2015, Brown University

 In this thesis we address the problem of building shape models of the human body, in 2D and 3D, which are realistic and efficient to… (more)

Subjects/Keywords: human body model; shape model; computer vision

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APA (6th Edition):

Zuffi, S. (2015). Shape Models of the Human Body for Distributed Inference. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:419434/

Chicago Manual of Style (16th Edition):

Zuffi, Silvia. “Shape Models of the Human Body for Distributed Inference.” 2015. Doctoral Dissertation, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:419434/.

MLA Handbook (7th Edition):

Zuffi, Silvia. “Shape Models of the Human Body for Distributed Inference.” 2015. Web. 15 Sep 2019.

Vancouver:

Zuffi S. Shape Models of the Human Body for Distributed Inference. [Internet] [Doctoral dissertation]. Brown University; 2015. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:419434/.

Council of Science Editors:

Zuffi S. Shape Models of the Human Body for Distributed Inference. [Doctoral Dissertation]. Brown University; 2015. Available from: https://repository.library.brown.edu/studio/item/bdr:419434/

3. Chua, Jeroen. Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding.

Degree: Department of Computer Science, 2017, Brown University

 We propose a general-purpose probabilistic framework for scene understanding tasks. We show that several classical scene understanding tasks can be modeled and addressed under a… (more)

Subjects/Keywords: Machine Learning

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APA (6th Edition):

Chua, J. (2017). Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:792615/

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):

Chua, Jeroen. “Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding.” 2017. Thesis, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:792615/.

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

MLA Handbook (7th Edition):

Chua, Jeroen. “Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding.” 2017. Web. 15 Sep 2019.

Vancouver:

Chua J. Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding. [Internet] [Thesis]. Brown University; 2017. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:792615/.

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

Council of Science Editors:

Chua J. Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding. [Thesis]. Brown University; 2017. Available from: https://repository.library.brown.edu/studio/item/bdr:792615/

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

4. Ren, Zhile. Semantic Three-Dimensional Understanding of Dynamic Scenes.

Degree: Department of Computer Science, 2018, Brown University

 We develop new representations and algorithms for three-dimensional (3D) scene understanding from images and videos. To model cluttered indoor scenes, we introduce object descriptors that… (more)

Subjects/Keywords: Machine Learning

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APA (6th Edition):

Ren, Z. (2018). Semantic Three-Dimensional Understanding of Dynamic Scenes. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:792891/

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):

Ren, Zhile. “Semantic Three-Dimensional Understanding of Dynamic Scenes.” 2018. Thesis, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:792891/.

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

MLA Handbook (7th Edition):

Ren, Zhile. “Semantic Three-Dimensional Understanding of Dynamic Scenes.” 2018. Web. 15 Sep 2019.

Vancouver:

Ren Z. Semantic Three-Dimensional Understanding of Dynamic Scenes. [Internet] [Thesis]. Brown University; 2018. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:792891/.

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

Council of Science Editors:

Ren Z. Semantic Three-Dimensional Understanding of Dynamic Scenes. [Thesis]. Brown University; 2018. Available from: https://repository.library.brown.edu/studio/item/bdr:792891/

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

5. Pacheco, Jason L. Variational Approximations with Diverse Applications.

Degree: PhD, Computer Science, 2016, Brown University

 We develop a family of algorithms for statistical inference in models of high dimensional continuous random variables. Our approach builds on existing variational methods, which… (more)

Subjects/Keywords: graphical models

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APA (6th Edition):

Pacheco, J. L. (2016). Variational Approximations with Diverse Applications. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:674262/

Chicago Manual of Style (16th Edition):

Pacheco, Jason L. “Variational Approximations with Diverse Applications.” 2016. Doctoral Dissertation, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:674262/.

MLA Handbook (7th Edition):

Pacheco, Jason L. “Variational Approximations with Diverse Applications.” 2016. Web. 15 Sep 2019.

Vancouver:

Pacheco JL. Variational Approximations with Diverse Applications. [Internet] [Doctoral dissertation]. Brown University; 2016. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:674262/.

Council of Science Editors:

Pacheco JL. Variational Approximations with Diverse Applications. [Doctoral Dissertation]. Brown University; 2016. Available from: https://repository.library.brown.edu/studio/item/bdr:674262/

6. Naderi Parizi, Sobhan. Modeling and Optimization of Classifiers with Latent Variables.

Degree: PhD, Electrical Sciences and Computer Engineering, 2016, Brown University

 Many applications in Computer Vision and Machine Learning entail learning from partially annotated data. A popular family of models that can capture unobserved variables in… (more)

Subjects/Keywords: optimization

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APA (6th Edition):

Naderi Parizi, S. (2016). Modeling and Optimization of Classifiers with Latent Variables. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:674189/

Chicago Manual of Style (16th Edition):

Naderi Parizi, Sobhan. “Modeling and Optimization of Classifiers with Latent Variables.” 2016. Doctoral Dissertation, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:674189/.

MLA Handbook (7th Edition):

Naderi Parizi, Sobhan. “Modeling and Optimization of Classifiers with Latent Variables.” 2016. Web. 15 Sep 2019.

Vancouver:

Naderi Parizi S. Modeling and Optimization of Classifiers with Latent Variables. [Internet] [Doctoral dissertation]. Brown University; 2016. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:674189/.

Council of Science Editors:

Naderi Parizi S. Modeling and Optimization of Classifiers with Latent Variables. [Doctoral Dissertation]. Brown University; 2016. Available from: https://repository.library.brown.edu/studio/item/bdr:674189/

7. Hughes, Michael C. Reliable and scalable variational inference for nonparametric mixtures, topics, and sequences.

Degree: PhD, Computer Science, 2016, Brown University

 We develop new algorithms for training nonparametric clustering models based on the Dirichlet Process (DP), including DP mixture models, hierarchical Dirichlet process (HDP) topic models,… (more)

Subjects/Keywords: Bayesian nonparametrics

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APA (6th Edition):

Hughes, M. C. (2016). Reliable and scalable variational inference for nonparametric mixtures, topics, and sequences. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:674327/

Chicago Manual of Style (16th Edition):

Hughes, Michael C. “Reliable and scalable variational inference for nonparametric mixtures, topics, and sequences.” 2016. Doctoral Dissertation, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:674327/.

MLA Handbook (7th Edition):

Hughes, Michael C. “Reliable and scalable variational inference for nonparametric mixtures, topics, and sequences.” 2016. Web. 15 Sep 2019.

Vancouver:

Hughes MC. Reliable and scalable variational inference for nonparametric mixtures, topics, and sequences. [Internet] [Doctoral dissertation]. Brown University; 2016. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:674327/.

Council of Science Editors:

Hughes MC. Reliable and scalable variational inference for nonparametric mixtures, topics, and sequences. [Doctoral Dissertation]. Brown University; 2016. Available from: https://repository.library.brown.edu/studio/item/bdr:674327/

8. Ghosh, Soumya. Bayesian Nonparametric Discovery of Layers and Parts from Scenes and Objects.

Degree: PhD, Computer Science, 2015, Brown University

 We develop statistical methods for analyzing natural images, videos, motion capture (MoCap) sequences, and three-dimensional (3D) representations of articulated objects. Our goal is to discover… (more)

Subjects/Keywords: Bayesian nonparametrics

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APA (6th Edition):

Ghosh, S. (2015). Bayesian Nonparametric Discovery of Layers and Parts from Scenes and Objects. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:419552/

Chicago Manual of Style (16th Edition):

Ghosh, Soumya. “Bayesian Nonparametric Discovery of Layers and Parts from Scenes and Objects.” 2015. Doctoral Dissertation, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:419552/.

MLA Handbook (7th Edition):

Ghosh, Soumya. “Bayesian Nonparametric Discovery of Layers and Parts from Scenes and Objects.” 2015. Web. 15 Sep 2019.

Vancouver:

Ghosh S. Bayesian Nonparametric Discovery of Layers and Parts from Scenes and Objects. [Internet] [Doctoral dissertation]. Brown University; 2015. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:419552/.

Council of Science Editors:

Ghosh S. Bayesian Nonparametric Discovery of Layers and Parts from Scenes and Objects. [Doctoral Dissertation]. Brown University; 2015. Available from: https://repository.library.brown.edu/studio/item/bdr:419552/

9. Swanson, Ben. Computationally Connecting Language Transfer and Second Language Education.

Degree: PhD, Computer Science, 2016, Brown University

 We explore the role of software assistance in native language targeted second language education. Beginning with the classification task of determining an author’s native language… (more)

Subjects/Keywords: Contrastive Analysis

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APA (6th Edition):

Swanson, B. (2016). Computationally Connecting Language Transfer and Second Language Education. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:674219/

Chicago Manual of Style (16th Edition):

Swanson, Ben. “Computationally Connecting Language Transfer and Second Language Education.” 2016. Doctoral Dissertation, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:674219/.

MLA Handbook (7th Edition):

Swanson, Ben. “Computationally Connecting Language Transfer and Second Language Education.” 2016. Web. 15 Sep 2019.

Vancouver:

Swanson B. Computationally Connecting Language Transfer and Second Language Education. [Internet] [Doctoral dissertation]. Brown University; 2016. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:674219/.

Council of Science Editors:

Swanson B. Computationally Connecting Language Transfer and Second Language Education. [Doctoral Dissertation]. Brown University; 2016. Available from: https://repository.library.brown.edu/studio/item/bdr:674219/

10. Kim, Daeil. Scalable Bayesian Nonparametric Models for Networks and Documents.

Degree: Department of Computer Science, 2016, Brown University

 We develop Bayesian nonparametric statistical models of document collections and social networks. Extending classic parametric topic models of documents, and stochastic block models of networks,… (more)

Subjects/Keywords: Bayesian Nonparametrics

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APA (6th Edition):

Kim, D. (2016). Scalable Bayesian Nonparametric Models for Networks and Documents. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:733381/

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):

Kim, Daeil. “Scalable Bayesian Nonparametric Models for Networks and Documents.” 2016. Thesis, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:733381/.

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

MLA Handbook (7th Edition):

Kim, Daeil. “Scalable Bayesian Nonparametric Models for Networks and Documents.” 2016. Web. 15 Sep 2019.

Vancouver:

Kim D. Scalable Bayesian Nonparametric Models for Networks and Documents. [Internet] [Thesis]. Brown University; 2016. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:733381/.

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

Council of Science Editors:

Kim D. Scalable Bayesian Nonparametric Models for Networks and Documents. [Thesis]. Brown University; 2016. Available from: https://repository.library.brown.edu/studio/item/bdr:733381/

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

11. Sun, Libin. The Devil is in the Details: Example-based Image Restoration and Detail Synthesis.

Degree: PhD, Computer Science, 2016, Brown University

 In our modern digital age, camera-equipped gadgets such as smart-phones and tablet devices let people capture and share increasing amounts of digital image data. However,… (more)

Subjects/Keywords: image restoration

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APA (6th Edition):

Sun, L. (2016). The Devil is in the Details: Example-based Image Restoration and Detail Synthesis. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:674410/

Chicago Manual of Style (16th Edition):

Sun, Libin. “The Devil is in the Details: Example-based Image Restoration and Detail Synthesis.” 2016. Doctoral Dissertation, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:674410/.

MLA Handbook (7th Edition):

Sun, Libin. “The Devil is in the Details: Example-based Image Restoration and Detail Synthesis.” 2016. Web. 15 Sep 2019.

Vancouver:

Sun L. The Devil is in the Details: Example-based Image Restoration and Detail Synthesis. [Internet] [Doctoral dissertation]. Brown University; 2016. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:674410/.

Council of Science Editors:

Sun L. The Devil is in the Details: Example-based Image Restoration and Detail Synthesis. [Doctoral Dissertation]. Brown University; 2016. Available from: https://repository.library.brown.edu/studio/item/bdr:674410/

12. Malitsky, Yuri. Instance-Specific Algorithm Configuration.

Degree: PhD, Computer Science, 2012, Brown University

 When developing a new heuristic or complete algorithm for a constraint satisfaction or constrained optimization problem, we frequently face the problem of choice. There may… (more)

Subjects/Keywords: algorithm configuration

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APA (6th Edition):

Malitsky, Y. (2012). Instance-Specific Algorithm Configuration. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:297609/

Chicago Manual of Style (16th Edition):

Malitsky, Yuri. “Instance-Specific Algorithm Configuration.” 2012. Doctoral Dissertation, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:297609/.

MLA Handbook (7th Edition):

Malitsky, Yuri. “Instance-Specific Algorithm Configuration.” 2012. Web. 15 Sep 2019.

Vancouver:

Malitsky Y. Instance-Specific Algorithm Configuration. [Internet] [Doctoral dissertation]. Brown University; 2012. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:297609/.

Council of Science Editors:

Malitsky Y. Instance-Specific Algorithm Configuration. [Doctoral Dissertation]. Brown University; 2012. Available from: https://repository.library.brown.edu/studio/item/bdr:297609/

13. Patterson, Genevieve M. Collective Insight: Crowd-driven Image Understanding.

Degree: PhD, Computer Science, 2016, Brown University

 Crowdsourced training data has become a mainstay in computer vision. Some of the most significant discoveries of the last few years were made possible by… (more)

Subjects/Keywords: visual attributes

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APA (6th Edition):

Patterson, G. M. (2016). Collective Insight: Crowd-driven Image Understanding. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:674340/

Chicago Manual of Style (16th Edition):

Patterson, Genevieve M. “Collective Insight: Crowd-driven Image Understanding.” 2016. Doctoral Dissertation, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:674340/.

MLA Handbook (7th Edition):

Patterson, Genevieve M. “Collective Insight: Crowd-driven Image Understanding.” 2016. Web. 15 Sep 2019.

Vancouver:

Patterson GM. Collective Insight: Crowd-driven Image Understanding. [Internet] [Doctoral dissertation]. Brown University; 2016. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:674340/.

Council of Science Editors:

Patterson GM. Collective Insight: Crowd-driven Image Understanding. [Doctoral Dissertation]. Brown University; 2016. Available from: https://repository.library.brown.edu/studio/item/bdr:674340/

14. Choe, Do Kook. Toward Solving Penn Treebank Parsing.

Degree: Department of Computer Science, 2017, Brown University

 A natural language parser recovers the latent grammatical structures of sentences. In many natural language processing (NLP) applications, parsing is applied to sentences first and… (more)

Subjects/Keywords: Natural language processing (Computer science)

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APA (6th Edition):

Choe, D. K. (2017). Toward Solving Penn Treebank Parsing. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:733298/

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):

Choe, Do Kook. “Toward Solving Penn Treebank Parsing.” 2017. Thesis, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:733298/.

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

MLA Handbook (7th Edition):

Choe, Do Kook. “Toward Solving Penn Treebank Parsing.” 2017. Web. 15 Sep 2019.

Vancouver:

Choe DK. Toward Solving Penn Treebank Parsing. [Internet] [Thesis]. Brown University; 2017. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:733298/.

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

Council of Science Editors:

Choe DK. Toward Solving Penn Treebank Parsing. [Thesis]. Brown University; 2017. Available from: https://repository.library.brown.edu/studio/item/bdr:733298/

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

15. Wiecki, Thomas V. Computational Psychiatry: Combining multiple levels of analysis to understand brain disorders.

Degree: PhD, Psychology, 2014, Brown University

 The premise of the emerging field of computational psychiatry is to use models from computational cognitive neuroscience to gain deeper insights into mental illness. In… (more)

Subjects/Keywords: computational psychiatry

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APA (6th Edition):

Wiecki, T. V. (2014). Computational Psychiatry: Combining multiple levels of analysis to understand brain disorders. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:419389/

Chicago Manual of Style (16th Edition):

Wiecki, Thomas V. “Computational Psychiatry: Combining multiple levels of analysis to understand brain disorders.” 2014. Doctoral Dissertation, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:419389/.

MLA Handbook (7th Edition):

Wiecki, Thomas V. “Computational Psychiatry: Combining multiple levels of analysis to understand brain disorders.” 2014. Web. 15 Sep 2019.

Vancouver:

Wiecki TV. Computational Psychiatry: Combining multiple levels of analysis to understand brain disorders. [Internet] [Doctoral dissertation]. Brown University; 2014. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:419389/.

Council of Science Editors:

Wiecki TV. Computational Psychiatry: Combining multiple levels of analysis to understand brain disorders. [Doctoral Dissertation]. Brown University; 2014. Available from: https://repository.library.brown.edu/studio/item/bdr:419389/

16. Freifeld, Oren. Statistics on Manifolds with Applications to Modeling Shape Deformations.

Degree: PhD, Applied Mathematics, 2013, Brown University

 Statistical models of non-rigid deformable shape have wide application in many fields, including computer vision, computer graphics, and biometry. We show that shape deformations are… (more)

Subjects/Keywords: statistical deformable-shape models

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APA (6th Edition):

Freifeld, O. (2013). Statistics on Manifolds with Applications to Modeling Shape Deformations. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:386129/

Chicago Manual of Style (16th Edition):

Freifeld, Oren. “Statistics on Manifolds with Applications to Modeling Shape Deformations.” 2013. Doctoral Dissertation, Brown University. Accessed September 15, 2019. https://repository.library.brown.edu/studio/item/bdr:386129/.

MLA Handbook (7th Edition):

Freifeld, Oren. “Statistics on Manifolds with Applications to Modeling Shape Deformations.” 2013. Web. 15 Sep 2019.

Vancouver:

Freifeld O. Statistics on Manifolds with Applications to Modeling Shape Deformations. [Internet] [Doctoral dissertation]. Brown University; 2013. [cited 2019 Sep 15]. Available from: https://repository.library.brown.edu/studio/item/bdr:386129/.

Council of Science Editors:

Freifeld O. Statistics on Manifolds with Applications to Modeling Shape Deformations. [Doctoral Dissertation]. Brown University; 2013. Available from: https://repository.library.brown.edu/studio/item/bdr:386129/

.