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ORCIDDaniel A. Keim
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- affiliation: University of Konstanz, Germany
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2020 – today
- 2024
[j181]Johannes Fuchs
, Frederik L. Dennig, Maria-Viktoria Heinle, Daniel A. Keim, Sara Di Bartolomeo:
Exploring the Design Space of BioFabric Visualization for Multivariate Network Analysis. Comput. Graph. Forum 43(3) (2024)- [j180]Thilo Spinner, Rebecca Kehlbeck, Rita Sevastjanova, Tobias Stähle, Daniel A. Keim, Oliver Deussen, Mennatallah El-Assady:
-generAItor: Tree-in-the-loop Text Generation for Language Model Explainability and Adaptation. ACM Trans. Interact. Intell. Syst. 14(2): 14 (2024) - [j179]Julius Rauscher, Raphael Buchmüller, Daniel A. Keim, Matthias Miller:
SkiVis: Visual Exploration and Route Planning in Ski Resorts. IEEE Trans. Vis. Comput. Graph. 30(1): 869-879 (2024) - [j178]Nils Rodrigues, Frederik L. Dennig, Vincent Brandt, Daniel A. Keim, Daniel Weiskopf:
Comparative Evaluation of Animated Scatter Plot Transitions. IEEE Trans. Vis. Comput. Graph. 30(6): 2929-2941 (2024) - [j177]Amyra Meidiana, Seok-Hee Hong, Peter Eades, Daniel A. Keim:
Automorphism Faithfulness Metrics for Symmetric Graph Drawings. IEEE Trans. Vis. Comput. Graph. 30(7): 3241-3255 (2024) - [j176]Frederik L. Dennig, Matthias Miller, Daniel A. Keim, Mennatallah El-Assady:
FS/DS: A Theoretical Framework for the Dual Analysis of Feature Space and Data Space. IEEE Trans. Vis. Comput. Graph. 30(8): 5165-5182 (2024) - [c294]Lucas Joos, Bastian Jäckl, Daniel A. Keim, Maximilian T. Fischer, Ladislav Peska, Jakub Lokoc:
Known-Item Search in Video: An Eye Tracking-Based Study. ICMR 2024: 311-319 - [c293]Shijun Cai, Seok-Hee Hong, Amyra Meidiana, Peter Eades, Daniel A. Keim:
Cluster-Faithful Graph Visualization: New Metrics and Algorithms. PacificVis 2024: 192-201 - [c292]Mohsen Jenadeleh, Frederik L. Dennig, René Cutura, Quynh Quang Ngo, Daniel A. Keim, Michael Sedlmair, Dietmar Saupe:
An Image Quality Dataset with Triplet Comparisons for Multi-dimensional Scaling. QoMEX 2024: 278-281 - [c291]Mark-Matthias Zymla, Raphael Buchmüller, Miriam Butt, Daniel A. Keim:
Deciphering Personal Argument Styles - A Comprehensive Approach to Analyzing Linguistic Properties of Argument Preferences. RATIO 2024: 296-314 - [c290]Lucas Joos, Uzay Durdu, Jonathan Wieland, Harald Reiterer, Daniel A. Keim, Johannes Fuchs, Maximilian T. Fischer:
Evaluating Node Selection Techniques for Network Visualizations in Virtual Reality. SUI 2024: 25:1-25:11 - [d4]Frederik L. Dennig, Lucas Joos, Patrick Paetzold, Daniela Blumberg, Oliver Deussen, Daniel A. Keim, Maximilian T. Fischer:
The Categorical Data Map - Replication Data. DaRUS, 2024
- [d3]Nils Rodrigues, Frederik L. Dennig, Vincent Brandt, Daniel A. Keim, Daniel Weiskopf:
Comparative Evaluation of Animated Scatter Plot Transitions - Supplemental Material. DaRUS, 2024 - [i63]Maximilian T. Fischer, Yannick Metz, Lucas Joos, Matthias Miller, Daniel A. Keim:
MULTI-CASE: A Transformer-based Ethics-aware Multimodal Investigative Intelligence Framework. CoRR abs/2401.01955 (2024) - [i62]Nils Rodrigues, Frederik L. Dennig, Vincent Brandt, Daniel A. Keim, Daniel Weiskopf:
Comparative Evaluation of Animated Scatter Plot Transitions. CoRR abs/2401.04692 (2024) - [i61]Thilo Spinner, Rebecca Kehlbeck, Rita Sevastjanova, Tobias Stähle, Daniel A. Keim, Oliver Deussen, Mennatallah El-Assady:
generAItor: Tree-in-the-Loop Text Generation for Language Model Explainability and Adaptation. CoRR abs/2403.07627 (2024) - [i60]Frederik L. Dennig, Lucas Joos, Patrick Paetzold, Daniela Blumberg, Oliver Deussen, Daniel A. Keim, Maximilian T. Fischer:
Toward the Categorical Data Map. CoRR abs/2404.16044 (2024) - [i59]Matthias Miller, Daniel Fürst, Maximilian T. Fischer, Hanna Hauptmann, Daniel A. Keim, Mennatallah El-Assady:
MelodyVis: Visual Analytics for Melodic Patterns in Sheet Music. CoRR abs/2407.05427 (2024) - [i58]Lucas Joos, Daniel A. Keim, Maximilian T. Fischer:
Cutting Through the Clutter: The Potential of LLMs for Efficient Filtration in Systematic Literature Reviews. CoRR abs/2407.10652 (2024) - [i57]Yannick Metz, Dennis Ackermann, Daniel A. Keim, Maximilian T. Fischer:
Interactive Public Transport Infrastructure Analysis through Mobility Profiles: Making the Mobility Transition Transparent. CoRR abs/2407.10791 (2024) - [i56]Udo Schlegel, Daniel A. Keim, Tobias Sutter:
Finding the DeepDream for Time Series: Activation Maximization for Univariate Time Series. CoRR abs/2408.10628 (2024) - [i55]Udo Schlegel, Julius Rauscher, Daniel A. Keim:
Interactive Counterfactual Generation for Univariate Time Series. CoRR abs/2408.10633 (2024) - [i54]Udo Schlegel, Daniel A. Keim:
Interactive dense pixel visualizations for time series and model attribution explanations. CoRR abs/2408.15073 (2024) - 2023
- [j175]Aoyu Wu, Dazhen Deng, Min Chen, Shixia Liu, Daniel A. Keim, Ross Maciejewski, Silvia Miksch, Hendrik Strobelt, Fernanda B. Viégas, Martin Wattenberg:
Grand Challenges in Visual Analytics Applications. IEEE Computer Graphics and Applications 43(5): 83-90 (2023) - [j174]Yannick Metz, Eugene Bykovets, Lucas Joos, Daniel A. Keim, Mennatallah El-Assady:
VISITOR: Visual Interactive State Sequence Exploration for Reinforcement Learning. Comput. Graph. Forum 42(3): 397-408 (2023) - [j173]Wolfgang Jentner, Giuliana Lindholz, Hanna Hauptmann, Mennatallah El-Assady, Kwan-Liu Ma, Daniel A. Keim:
Visual Analytics of Co-Occurrences to Discover Subspaces in Structured Data. ACM Trans. Interact. Intell. Syst. 13(2): 10:1-10:49 (2023) - [j172]Daniel Seebacher, Tom Polk, Halldor Janetzko, Daniel A. Keim, Tobias Schreck, Manuel Stein:
Investigating the Sketchplan: A Novel Way of Identifying Tactical Behavior in Massive Soccer Datasets. IEEE Trans. Vis. Comput. Graph. 29(4): 1920-1936 (2023) - [c289]Lucas Joos, Karsten Klein, Maximilian T. Fischer, Frederik L. Dennig, Daniel A. Keim, Michael Krone:
Exploring Trajectory Data in Augmented Reality: A Comparative Study of Interaction Modalities. ISMAR 2023: 790-799 - [c288]Udo Schlegel, Daniel A. Keim:
Interactive Dense Pixel Visualizations for Time Series and Model Attribution Explanations. MLVis@EuroVis 2023: 1-5 - [c287]Lucas Joos, Maximilian T. Fischer, Daniel A. Keim, Johannes Fuchs:
Aesthetic-Driven Navigation for Node-Link Diagrams in VR. SUI 2023: 25:1-25:10 - [c286]Udo Schlegel, Daniel A. Keim:
A Deep Dive into Perturbations as Evaluation Technique for Time Series XAI. xAI (3) 2023: 165-180 - [d2]David Pomerenke, Frederik L. Dennig, Daniel A. Keim, Johannes Fuchs, Michael Blumenschein:
Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters". 2.0. DaRUS, 2023 [all versions] - [d1]David Pomerenke, Frederik L. Dennig, Daniel A. Keim, Johannes Fuchs, Michael Blumenschein:
Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters". 2.1. DaRUS, 2023 [all versions] - [i53]Richard Brath, Daniel A. Keim, Johannes Knittel, Shimei Pan, Pia Sommerauer, Hendrik Strobelt:
The Role of Interactive Visualization in Explaining (Large) NLP Models: from Data to Inference. CoRR abs/2301.04528 (2023) - [i52]Udo Schlegel, Daniel A. Keim:
A Deep Dive into Perturbations as Evaluation Technique for Time Series XAI. CoRR abs/2307.05104 (2023) - [i51]Udo Schlegel, Daniela Oelke, Daniel A. Keim, Mennatallah El-Assady:
Visual Explanations with Attributions and Counterfactuals on Time Series Classification. CoRR abs/2307.08494 (2023) - [i50]Julius Rauscher, Raphael Buchmüller, Daniel A. Keim, Matthias Miller:
SkiVis: Visual Exploration and Route Planning in Ski Resorts. CoRR abs/2307.08570 (2023) - [i49]Yannick Metz, David Lindner, Raphaël Baur, Daniel A. Keim, Mennatallah El-Assady:
RLHF-Blender: A Configurable Interactive Interface for Learning from Diverse Human Feedback. CoRR abs/2308.04332 (2023) - [i48]Udo Schlegel, Daniel A. Keim:
Introducing the Attribution Stability Indicator: a Measure for Time Series XAI Attributions. CoRR abs/2310.04178 (2023) - [i47]Thilo Spinner, Rebecca Kehlbeck, Rita Sevastjanova, Tobias Stähle, Daniel A. Keim, Oliver Deussen, Andreas Spitz, Mennatallah El-Assady:
Revealing the Unwritten: Visual Investigation of Beam Search Trees to Address Language Model Prompting Challenges. CoRR abs/2310.11252 (2023) - 2022
- [j171]Matthias Kraus, Johannes Fuchs, Björn Sommer, Karsten Klein, Ulrich Engelke, Daniel A. Keim, Falk Schreiber:
Immersive Analytics with Abstract 3D Visualizations: A Survey. Comput. Graph. Forum 41(1): 201-229 (2022) - [j170]Matthias Miller, Daniel Fürst, Hanna Hauptmann, Daniel A. Keim, Mennatallah El-Assady:
Augmenting Digital Sheet Music through Visual Analytics. Comput. Graph. Forum 41(1): 301-316 (2022) - [j169]Matthias Miller, Julius Rauscher, Daniel A. Keim, Mennatallah El-Assady:
CorpusVis: Visual Analysis of Digital Sheet Music Collections. Comput. Graph. Forum 41(3): 283-294 (2022) - [j168]Quynh Quang Ngo, Frederik L. Dennig, Daniel A. Keim, Michael Sedlmair:
Machine learning meets visualization - Experiences and lessons learned. it Inf. Technol. 64(4-5): 169-180 (2022) - [j167]Dirk Streeb, Yannick Metz, Udo Schlegel, Bruno Schneider, Mennatallah El-Assady, Hansjörg Neth, Min Chen, Daniel A. Keim:
Task-Based Visual Interactive Modeling: Decision Trees and Rule-Based Classifiers. IEEE Trans. Vis. Comput. Graph. 28(9): 3307-3323 (2022) - [j166]Lucas Joos, Sabrina Jaeger-Honz, Falk Schreiber, Daniel A. Keim, Karsten Klein:
Visual Comparison of Networks in VR. IEEE Trans. Vis. Comput. Graph. 28(11): 3651-3661 (2022) - [j165]Rita Sevastjanova, Mennatallah El-Assady, Adam Bradley, Christopher Collins, Miriam Butt, Daniel A. Keim:
VisInReport: Complementing Visual Discourse Analytics Through Personalized Insight Reports. IEEE Trans. Vis. Comput. Graph. 28(12): 4757-4769 (2022) - [j164]Eren Cakmak, Dominik Jäckle, Tobias Schreck, Daniel A. Keim, Johannes Fuchs:
Multiscale Visualization: A Structured Literature Analysis. IEEE Trans. Vis. Comput. Graph. 28(12): 4918-4929 (2022) - [c285]Yannick Metz, Udo Schlegel, Daniel Seebacher, Mennatallah El-Assady, Daniel A. Keim:
A Comprehensive Workflow for Effective Imitation and Reinforcement Learning with Visual Analytics. EuroVA@EuroVis 2022: 19-23 - [c284]Maximilian T. Fischer, Simon David Hirsbrunner, Wolfgang Jentner, Matthias Miller, Daniel A. Keim, Paula Helm:
Promoting Ethical Awareness in Communication Analysis: Investigating Potentials and Limits of Visual Analytics for Intelligence Applications. FAccT 2022: 877-889 - [c283]Udo Schlegel, Samuel Schiegg, Daniel A. Keim:
ViNNPruner: Visual Interactive Pruning for Deep Learning. MLVis@EuroVis 2022: 13-17 - [c282]Julius Rauscher, Matthias Miller, Daniel A. Keim:
Visual Exploration of Preference-based Routes in Ski Resorts. EuroVis (Posters) 2022: 71-73 - [e10]Jan Bender, Mario Botsch, Daniel A. Keim:
VMV 2022, 27th International Symposium on Vision, Modeling, and Visualization, Konstanz, Germany, September 27-30, 2022. Eurographics Association 2022 [contents] - [i46]Maximilian T. Fischer, Simon David Hirsbrunner, Wolfgang Jentner, Matthias Miller, Daniel A. Keim, Paula Helm:
Promoting Ethical Awareness in Communication Analysis: Investigating Potentials and Limits of Visual Analytics for Intelligence Applications. CoRR abs/2203.09859 (2022) - [i45]Matthias Miller, Julius Rauscher, Daniel A. Keim, Mennatallah El-Assady:
CorpusVis: Visual Analysis of Digital Sheet Music Collections. CoRR abs/2203.12663 (2022) - [i44]Udo Schlegel, Samuel Schiegg, Daniel A. Keim:
ViNNPruner: Visual Interactive Pruning for Deep Learning. CoRR abs/2205.15731 (2022) - [i43]Eugene Bykovets, Yannick Metz, Mennatallah El-Assady, Daniel A. Keim, Joachim M. Buhmann:
BARReL: Bottleneck Attention for Adversarial Robustness in Vision-Based Reinforcement Learning. CoRR abs/2208.10481 (2022) - [i42]Eren Cakmak, Johannes Fuchs, Dominik Jäckle, Tobias Schreck, Ulrik Brandes, Daniel A. Keim:
Motif-Based Visual Analysis of Dynamic Networks. CoRR abs/2208.11932 (2022) - [i41]Eugene Bykovets, Yannick Metz, Mennatallah El-Assady, Daniel A. Keim, Joachim M. Buhmann:
How to Enable Uncertainty Estimation in Proximal Policy Optimization. CoRR abs/2210.03649 (2022) - [i40]Polo Chau, Alex Endert, Daniel A. Keim, Daniela Oelke:
Interactive Visualization for Fostering Trust in ML (Dagstuhl Seminar 22351). Dagstuhl Reports 12(8): 103-116 (2022) - 2021
- [j163]Fabian Sperrle, Astrik Jeitler, Jürgen Bernard, Daniel A. Keim, Mennatallah El-Assady:
Co-adaptive visual data analysis and guidance processes. Comput. Graph. 100: 93-105 (2021) - [j162]Juri F. Buchmüller, Udo Schlegel, Eren Cakmak, Daniel A. Keim, Evanthia Dimara:
SpatialRugs: A compact visualization of space and time for analyzing collective movement data. Comput. Graph. 101: 23-34 (2021) - [j161]Dirk Streeb, Mennatallah El-Assady, Daniel A. Keim, Min Chen:
Why Visualize? Arguments for Visual Support in Decision Making. IEEE Computer Graphics and Applications 41(2): 17-22 (2021) - [j160]Matthias Kraus, Karsten Klein, Johannes Fuchs, Daniel A. Keim, Falk Schreiber, Michael Sedlmair, Theresa-Marie Rhyne:
The Value of Immersive Visualization. IEEE Computer Graphics and Applications 41(4): 125-132 (2021) - [j159]Emma Beauxis-Aussalet, Michael Behrisch, Rita Borgo, Duen Horng Chau, Christopher Collins, David S. Ebert, Mennatallah El-Assady, Alex Endert, Daniel A. Keim, Jörn Kohlhammer, Daniela Oelke, Jaakko Peltonen, Maria Riveiro, Tobias Schreck, Hendrik Strobelt, Jarke J. van Wijk, Theresa-Marie Rhyne:
The Role of Interactive Visualization in Fostering Trust in AI. IEEE Computer Graphics and Applications 41(6): 7-12 (2021) - [j158]Maximilian T. Fischer, Daniel Seebacher, Rita Sevastjanova, Daniel A. Keim, Mennatallah El-Assady:
CommAID: Visual Analytics for Communication Analysis through Interactive Dynamics Modeling. Comput. Graph. Forum 40(3): 25-36 (2021) - [j157]Fabian Sperrle, Hanna Schäfer, Daniel A. Keim, Mennatallah El-Assady:
Learning Contextualized User Preferences for Co-Adaptive Guidance in Mixed-Initiative Topic Model Refinement. Comput. Graph. Forum 40(3): 215-226 (2021) - [j156]Frederik L. Dennig, Maximilian T. Fischer, Michael Blumenschein, Johannes Fuchs, Daniel A. Keim, Evanthia Dimara:
ParSetgnostics: Quality Metrics for Parallel Sets. Comput. Graph. Forum 40(3): 375-386 (2021) - [j155]Fabian Sperrle, Mennatallah El-Assady, Grace Guo, Rita Borgo, Duen Horng Chau, Alex Endert, Daniel A. Keim:
A Survey of Human-Centered Evaluations in Human-Centered Machine Learning. Comput. Graph. Forum 40(3): 543-567 (2021) - [j154]Bruno Schneider, Dominik Jäckle, Florian Stoffel, Alexandra Diehl, Johannes Fuchs, Daniel A. Keim:
Integrating Data and Model Space in Ensemble Learning by Visual Analytics. IEEE Trans. Big Data 7(3): 483-496 (2021) - [j153]Daniel Seebacher, Johannes Häußler, Michael Hundt, Manuel Stein, Hannes Müller, Ulrich Engelke, Daniel A. Keim:
Visual Analysis of Spatio-Temporal Event Predictions: Investigating the Spread Dynamics of Invasive Species. IEEE Trans. Big Data 7(3): 497-509 (2021) - [j152]Eren Cakmak, Udo Schlegel, Dominik Jäckle, Daniel A. Keim, Tobias Schreck:
Multiscale Snapshots: Visual Analysis of Temporal Summaries in Dynamic Graphs. IEEE Trans. Vis. Comput. Graph. 27(2): 517-527 (2021) - [j151]Maximilian T. Fischer, Devanshu Arya, Dirk Streeb, Daniel Seebacher, Daniel A. Keim, Marcel Worring:
Visual Analytics for Temporal Hypergraph Model Exploration. IEEE Trans. Vis. Comput. Graph. 27(2): 550-560 (2021) - [j150]Philipp Meschenmoser, Juri F. Buchmüller, Daniel Seebacher, Martin Wikelski, Daniel A. Keim:
MultiSegVA: Using Visual Analytics to Segment Biologging Time Series on Multiple Scales. IEEE Trans. Vis. Comput. Graph. 27(2): 1623-1633 (2021) - [j149]Dirk Streeb, Mennatallah El-Assady, Daniel A. Keim, Min Chen:
Why Visualize? Untangling a Large Network of Arguments. IEEE Trans. Vis. Comput. Graph. 27(3): 2220-2236 (2021) - [c281]Thilo Spinner, Udo Schlegel, Martin Schall, Fabian Sperrle, Rita Sevastjanova, Beatrice Gobbo, Julius Rauscher, Mennatallah El-Assady, Daniel A. Keim:
Speculative Execution of Similarity Queries: Real-Time Parameter Optimization through Visual Exploration. EDBT/ICDT Workshops 2021 - [c280]Eren Cakmak, Manuel Plank, Daniel S. Calovi, Alex Jordan, Daniel A. Keim:
Spatio-temporal clustering benchmark for collective animal behavior. HANIMOB@SIGSPATIAL 2021: 5-8 - [c279]Udo Schlegel, Duy Vo Lam, Daniel A. Keim, Daniel Seebacher:
TS-MULE: Local Interpretable Model-Agnostic Explanations for Time Series Forecast Models. PKDD/ECML Workshops (1) 2021: 5-14 - [c278]Maximilian T. Fischer, Alexander Frings, Daniel A. Keim, Daniel Seebacher:
Towards a Survey on Static and Dynamic Hypergraph Visualizations. IEEE VIS (Short Papers) 2021: 81-85 - [c277]Frederik L. Dennig, Eren Cakmak, Henrik Plate, Daniel A. Keim:
VulnEx: Exploring Open-Source Software Vulnerabilities in Large Development Organizations to Understand Risk Exposure. VizSec 2021: 79-83 - [i39]Maximilian T. Fischer, Daniel A. Keim, Manuel Stein:
Video-based Analysis of Soccer Matches. CoRR abs/2105.04875 (2021) - [i38]Daniel Seebacher, Maximilian T. Fischer, Rita Sevastjanova, Daniel A. Keim, Mennatallah El-Assady:
Visual Analytics of Conversational Dynamics. CoRR abs/2105.04897 (2021) - [i37]Maximilian T. Fischer, Daniel Seebacher, Rita Sevastjanova, Daniel A. Keim, Mennatallah El-Assady:
CommAID: Visual Analytics for Communication Analysis through Interactive Dynamics Modeling. CoRR abs/2106.06334 (2021) - [i36]Maximilian T. Fischer, Frederik L. Dennig, Daniel Seebacher, Daniel A. Keim, Mennatallah El-Assady:
Communication Analysis through Visual Analytics: Current Practices, Challenges, and New Frontiers. CoRR abs/2106.14802 (2021) - [i35]Maximilian T. Fischer, Alexander Frings, Daniel A. Keim, Daniel Seebacher:
Towards a Survey on Static and Dynamic Hypergraph Visualizations. CoRR abs/2107.13936 (2021) - [i34]Frederik L. Dennig, Eren Cakmak, Henrik Plate, Daniel A. Keim:
VulnEx: Exploring Open-Source Software Vulnerabilities in Large Development Organizations to Understand Risk Exposure. CoRR abs/2108.06259 (2021) - [i33]Udo Schlegel, Duy Vo Lam, Daniel A. Keim, Daniel Seebacher:
TS-MULE: Local Interpretable Model-Agnostic Explanations for Time Series Forecast Models. CoRR abs/2109.08438 (2021) - [i32]Udo Schlegel, Daniel A. Keim:
Time Series Model Attribution Visualizations as Explanations. CoRR abs/2109.12935 (2021) - 2020
- [j148]Johannes Fuchs, Petra Isenberg, Anastasia Bezerianos, Matthias Miller, Daniel A. Keim, Beatriz Sousa Santos, Ginger Alford:
Teaching Clustering Algorithms With EduClust: Experience Report and Future Directions. IEEE Computer Graphics and Applications 40(2): 98-102 (2020) - [j147]Eren Cakmak, Hanna Schäfer, Juri Buchmüller, Johannes Fuchs, Tobias Schreck, Alex Jordan, Daniel A. Keim:
MotionGlyphs: Visual Abstraction of Spatio-Temporal Networks in Collective Animal Behavior. Comput. Graph. Forum 39(3): 63-75 (2020) - [j146]Michael Blumenschein, Xuan Zhang, David Pomerenke, Daniel A. Keim, Johannes Fuchs:
Evaluating Reordering Strategies for Cluster Identification in Parallel Coordinates. Comput. Graph. Forum 39(3): 537-549 (2020) - [j145]Michael Blumenschein, Luka J. Debbeler, Nadine C. Lages, Britta Renner, Daniel A. Keim, Mennatallah El-Assady:
v-plots: Designing Hybrid Charts for the Comparative Analysis of Data Distributions. Comput. Graph. Forum 39(3): 565-577 (2020) - [j144]Matthias Kraus, Thomas Pollok, Matthias Miller, Timon Urs Kilian, Tobias Moritz, Daniel Schweitzer, Jürgen Beyerer, Daniel A. Keim, Chengchao Qu, Wolfgang Jentner:
Toward Mass Video Data Analysis: Interactive and Immersive 4D Scene Reconstruction. Sensors 20(18): 5426 (2020) - [j143]Matthias Kraus, Niklas Weiler, Daniela Oelke, Johannes Kehrer, Daniel A. Keim, Johannes Fuchs:
The Impact of Immersion on Cluster Identification Tasks. IEEE Trans. Vis. Comput. Graph. 26(1): 525-535 (2020) - [j142]Mennatallah El-Assady, Rebecca Kehlbeck, Christopher Collins, Daniel A. Keim, Oliver Deussen:
Semantic Concept Spaces: Guided Topic Model Refinement using Word-Embedding Projections. IEEE Trans. Vis. Comput. Graph. 26(1): 1001-1011 (2020) - [c276]Amyra Meidiana, Seok-Hee Hong, Peter Eades, Daniel A. Keim:
Quality Metrics for Symmetric Graph Drawings. PacificVis 2020: 11-15 - [c275]Matthias Kraus, Katrin Angerbauer, Juri Buchmüller, Daniel Schweitzer, Daniel A. Keim, Michael Sedlmair, Johannes Fuchs:
Assessing 2D and 3D Heatmaps for Comparative Analysis: An Empirical Study. CHI 2020: 1-14 - [c274]Juri F. Buchmüller, Udo Schlegel, Eren Cakmak, Daniel A. Keim, Evanthia Dimara:
SpatialRugs: Enhancing Spatial Awareness of Movement in Dense Pixel Visualizations. EuroVA@Eurographics/EuroVis 2020: 1-5 - [c273]Fabian Sperrle, Astrik Jeitler, Jürgen Bernard, Daniel A. Keim, Mennatallah El-Assady:
Learning and Teaching in Co-Adaptive Guidance for Mixed-Initiative Visual Analytics. EuroVA@Eurographics/EuroVis 2020: 61-65 - [c272]Bruno Schneider, Daniel A. Keim, Mennatallah El-Assady:
DataShiftExplorer: Visualizing and Comparing Change in Multidimensional Data for Supervised Learning. VISIGRAPP (3: IVAPP) 2020: 141-148 - [c271]Matthias Kraus, Hanna Schäfer, Philipp Meschenmoser, Daniel Schweitzer, Daniel A. Keim, Michael Sedlmair, Johannes Fuchs:
A Comparative Study of Orientation Support Tools in Virtual Reality Environments with Virtual Teleportation. ISMAR 2020: 227-238 - [c270]Udo Schlegel, Eren Cakmak, Hiba Arnout, Mennatallah El-Assady, Daniela Oelke, Daniel A. Keim:
Towards visual debugging for multi-target time series classification. IUI 2020: 202-206 - [c269]Udo Schlegel, Eren Cakmak, Daniel A. Keim:
ModelSpeX: Model Specification Using Explainable Artificial Intelligence Methods. MLVis@Eurographics/EuroVis 2020: 7-11 - [i31]Juri F. Buchmüller, Udo Schlegel, Eren Cakmak, Evanthia Dimara, Daniel A. Keim:
SpatialRugs: Enhancing Spatial Awareness of Movement in Dense Pixel Visualizations. CoRR abs/2003.12282 (2020) - [i30]Maximilian T. Fischer, Devanshu Arya, Dirk Streeb, Daniel Seebacher, Daniel A. Keim, Marcel Worring:
Visual Analytics for Temporal Hypergraph Model Exploration. CoRR abs/2008.07299 (2020) - [i29]Eren Cakmak, Udo Schlegel, Dominik Jäckle, Daniel A. Keim, Tobias Schreck:
Multiscale Snapshots: Visual Analysis of Temporal Summaries in Dynamic Graphs. CoRR abs/2008.08282 (2020) - [i28]Philipp Meschenmoser, Juri F. Buchmüller, Daniel Seebacher, Martin Wikelski, Daniel A. Keim:
MultiSegVA: Using Visual Analytics to Segment Biologging Time Series on Multiple Scales. CoRR abs/2009.00548 (2020) - [i27]Daniel Fürst, Matthias Miller, Daniel A. Keim, Alexandra Bonnici, Hanna Schäfer, Mennatallah El-Assady:
Augmenting Sheet Music with Rhythmic Fingerprints. CoRR abs/2009.02057 (2020) - [i26]Fabian Sperrle, Mennatallah El-Assady, Grace Guo, Duen Horng Chau, Alex Endert, Daniel A. Keim:
Should We Trust (X)AI? Design Dimensions for Structured Experimental Evaluations. CoRR abs/2009.06433 (2020) - [i25]Eren Cakmak, Dominik Jäckle, Tobias Schreck, Daniel A. Keim:
dg2pix: Pixel-Based Visual Analysis of Dynamic Graphs. CoRR abs/2009.07322 (2020) - [i24]Alexandra Diehl, Matthias Kraus, Alfie Abdul-Rahman, Mennatallah El-Assady, Benjamin Bach, Robert S. Laramee, Daniel A. Keim, Min Chen:
Studying Visualization Guidelines According to Grounded Theory. CoRR abs/2010.09040 (2020) - [i23]Austin P. Wright, Zijie J. Wang, Haekyu Park, Grace Guo, Fabian Sperrle, Mennatallah El-Assady, Alex Endert, Daniel A. Keim, Duen Horng Chau:
A Comparative Analysis of Industry Human-AI Interaction Guidelines. CoRR abs/2010.11761 (2020) - [i22]Udo Schlegel, Daniela Oelke, Daniel A. Keim, Mennatallah El-Assady:
An Empirical Study of Explainable AI Techniques on Deep Learning Models For Time Series Tasks. CoRR abs/2012.04344 (2020) - [i21]