Interactive visual exploration of probabilistic models:
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Abschlussarbeit Buch |
| Sprache: | English German |
| Veröffentlicht: |
Jena
[2022]
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Inhaltsverzeichnis |
| Beschreibung: | Deutsche Kurzfassung: Seite v |
| Beschreibung: | ii, 111 Seiten, Seite iii-vii Illustrationen, Diagramme 30 cm |
Internformat
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Datensatz im Suchindex
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| adam_text |
Contents Contents î 1 Introduction 1 2 Background 5 2.1 Terminology. 5 2.2 Fundamentals of Visualization. 8 2.2.1 Visual Marks and Visual Channels. 11 2.2.2 Visualizing High-Dimensional Data. 13 2.3 Visualizing Multivariate Data. 17 2.4 Visualizing Multivariate Functions. 20 2.5 Visualizing Probability Distributions. 22 3 Visual Encoding of Multivariate Probability Distributions and Data 27 3.1 Basic Definitions. 29 3.2 Facets: Derived Visualizations.30 3.2.1 Density Facet. 30 3.2.2 Marginal Facet.35 3.2.3 Data/Samples Facet. 35 3.2.4 Aggregation Facet. 37 3.3 Aligning Data and Model Operations. 39 3.4 Aligning Data and Model Visualizations
. 40 3.5 Combining Facets. 41 3.6 Additional Visual Channels: Color, Shape, Size. 42 3.7 Design Choices for Visual Encoding. 44 3.7.1 Challenges.45 3.7.2 Design Goals. 45 3.7.3 Design Decisions . 45 4 Lumen: A Visual Interface for Probabilistic Models and Data 49 4.1 A Life Cycle for Probabilistic Models.50 4.2 Visual Analytics System Requirements. 54 4.3 The Visual Interface. 55 4.3.1 Schema Panel. 55 4.3.2 Specification Panel . 56 4.3.3 Dashboard. 57 4.3.4 Basic Workflow. 58 4.4 Step-by-Step Example. 58 4.5 Design
Considerations. 60 5 Applications 63 5.1 Using Lumen for Data-driven Probabilistic Modeling. 64 5.1.1 CG Distributions. 65 5.1.2 Sum-Product Networks.66 5.1.3 Simple Density Estimator.70 5.1.4 Exploration of a CG Model. 71 5.1.5 Modeling the Penguin Data Set.72 i
Contents Probabilistic Programming. 74 5.2.1 Bayesian/Probabilistic Expert System. 74 5.2.2 Probabilistic Programming. 75 5.2.3 Graphical Models. 76 5.2.4 Learning Graphical Models from Data. 76 5.2.5 Example Bayesian Network. Tl 5.2.6 Probabilistic Programming Languages. 78 5.2.7 A Workflow for Probabilistic Programming . 79 5.3 Using Lumen for Interactive Visual Synthesis of Probabilistic Programs 81 5.3.1 Synthesizing Probabilistic Programs.82 5.3.2 Visualizing Bayesian Networks using Lumen . 84 5.3.3 Probabilistic Model Graph .85 5.3.4 Demonstration. 86 5.4 Using Lumen for Probabilistic Programming. 90 5.4.1 Latent and Independent Variables.90 5.4.2 Extended Features. 91 5.4.3
Demonstration.92 5.2 6 Summary 99 Bibliography 101 Appendix iii Abstract. iii Kurzfassung. v Ehrenwörtliche Erklärung.vii ii |
| adam_txt |
Contents Contents î 1 Introduction 1 2 Background 5 2.1 Terminology. 5 2.2 Fundamentals of Visualization. 8 2.2.1 Visual Marks and Visual Channels. 11 2.2.2 Visualizing High-Dimensional Data. 13 2.3 Visualizing Multivariate Data. 17 2.4 Visualizing Multivariate Functions. 20 2.5 Visualizing Probability Distributions. 22 3 Visual Encoding of Multivariate Probability Distributions and Data 27 3.1 Basic Definitions. 29 3.2 Facets: Derived Visualizations.30 3.2.1 Density Facet. 30 3.2.2 Marginal Facet.35 3.2.3 Data/Samples Facet. 35 3.2.4 Aggregation Facet. 37 3.3 Aligning Data and Model Operations. 39 3.4 Aligning Data and Model Visualizations
. 40 3.5 Combining Facets. 41 3.6 Additional Visual Channels: Color, Shape, Size. 42 3.7 Design Choices for Visual Encoding. 44 3.7.1 Challenges.45 3.7.2 Design Goals. 45 3.7.3 Design Decisions . 45 4 Lumen: A Visual Interface for Probabilistic Models and Data 49 4.1 A Life Cycle for Probabilistic Models.50 4.2 Visual Analytics System Requirements. 54 4.3 The Visual Interface. 55 4.3.1 Schema Panel. 55 4.3.2 Specification Panel . 56 4.3.3 Dashboard. 57 4.3.4 Basic Workflow. 58 4.4 Step-by-Step Example. 58 4.5 Design
Considerations. 60 5 Applications 63 5.1 Using Lumen for Data-driven Probabilistic Modeling. 64 5.1.1 CG Distributions. 65 5.1.2 Sum-Product Networks.66 5.1.3 Simple Density Estimator.70 5.1.4 Exploration of a CG Model. 71 5.1.5 Modeling the Penguin Data Set.72 i
Contents Probabilistic Programming. 74 5.2.1 Bayesian/Probabilistic Expert System. 74 5.2.2 Probabilistic Programming. 75 5.2.3 Graphical Models. 76 5.2.4 Learning Graphical Models from Data. 76 5.2.5 Example Bayesian Network. Tl 5.2.6 Probabilistic Programming Languages. 78 5.2.7 A Workflow for Probabilistic Programming . 79 5.3 Using Lumen for Interactive Visual Synthesis of Probabilistic Programs 81 5.3.1 Synthesizing Probabilistic Programs.82 5.3.2 Visualizing Bayesian Networks using Lumen . 84 5.3.3 Probabilistic Model Graph .85 5.3.4 Demonstration. 86 5.4 Using Lumen for Probabilistic Programming. 90 5.4.1 Latent and Independent Variables.90 5.4.2 Extended Features. 91 5.4.3
Demonstration.92 5.2 6 Summary 99 Bibliography 101 Appendix iii Abstract. iii Kurzfassung. v Ehrenwörtliche Erklärung.vii ii |
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| author | Lucas, Philipp 1987- |
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| discipline | Informatik |
| discipline_str_mv | Informatik |
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| spelling | Lucas, Philipp 1987- Verfasser (DE-588)127347743X aut Interactive visual exploration of probabilistic models von Dipl.-Inf. Philipp Paul Thomas Lucas Jena [2022] ii, 111 Seiten, Seite iii-vii Illustrationen, Diagramme 30 cm txt rdacontent n rdamedia nc rdacarrier Deutsche Kurzfassung: Seite v Dissertation Friedrich-Schiller-Universität Jena 2022 Visualisierung (DE-588)4188417-6 gnd rswk-swf Graphische Benutzeroberfläche (DE-588)4275084-2 gnd rswk-swf Statistisches Modell (DE-588)4121722-6 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Visualisierung (DE-588)4188417-6 s Graphische Benutzeroberfläche (DE-588)4275084-2 s Statistisches Modell (DE-588)4121722-6 s DE-604 B:DE-101 application/pdf https://d-nb.info/1274370515/04 Inhaltsverzeichnis Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034237300&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p emasg 0,43446 20230314 DE-101 https://d-nb.info/provenance/plan#emasg |
| spellingShingle | Lucas, Philipp 1987- Interactive visual exploration of probabilistic models Visualisierung (DE-588)4188417-6 gnd Graphische Benutzeroberfläche (DE-588)4275084-2 gnd Statistisches Modell (DE-588)4121722-6 gnd |
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| title | Interactive visual exploration of probabilistic models |
| title_auth | Interactive visual exploration of probabilistic models |
| title_exact_search | Interactive visual exploration of probabilistic models |
| title_exact_search_txtP | Interactive visual exploration of probabilistic models |
| title_full | Interactive visual exploration of probabilistic models von Dipl.-Inf. Philipp Paul Thomas Lucas |
| title_fullStr | Interactive visual exploration of probabilistic models von Dipl.-Inf. Philipp Paul Thomas Lucas |
| title_full_unstemmed | Interactive visual exploration of probabilistic models von Dipl.-Inf. Philipp Paul Thomas Lucas |
| title_short | Interactive visual exploration of probabilistic models |
| title_sort | interactive visual exploration of probabilistic models |
| topic | Visualisierung (DE-588)4188417-6 gnd Graphische Benutzeroberfläche (DE-588)4275084-2 gnd Statistisches Modell (DE-588)4121722-6 gnd |
| topic_facet | Visualisierung Graphische Benutzeroberfläche Statistisches Modell Hochschulschrift |
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