Biblio
Making Sense of Scientific Simulation Ensembles With Semantic Interaction. Computer Graphics Forum. 2020;39.
Computer_Graphics_Forum copy.pdf (1.4 MB)
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Modelling the Effect of Computation Sampling on Insight Error in Computational Fluid Dynamics Scientific Simulation. Journal of Engineering, Design and Technology. 2020:32.
CFD_IE_Study.pdf (2.7 MB)
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NetReAct: Interactive Learning for Network Summarization. In: NeurIPS 2020 Workshop on Human and Model in the Loop Evaluation and Training Strategies (HAMLETS). NeurIPS 2020 Workshop on Human and Model in the Loop Evaluation and Training Strategies (HAMLETS). ; 2020. p. .
NetReact_NeuripsWorkshop (1).pdf (584.12 KB)
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The Smart Amplified Group Environment. In: 4th Workshop on Immersive Analytics at ACM CHI 2020. 4th Workshop on Immersive Analytics at ACM CHI 2020. ; 2020. p. 6.
09_IA2020-Submission9-Smart_Amplified_Group_Environment__The_future_of_SAGE.pdf (351.92 KB)

With Respect to What? Simultaneous Interaction with Dimension Reduction and Clustering Projections. In: Proceedings of the 25th International Conference on Intelligent User Interfaces. Proceedings of the 25th International Conference on Intelligent User Interfaces. New York, NY, USA; 2020. p. 177–188. Available from: https://doi.org/10.1145/3377325.3377516
With_Respect_to_What_.pdf (672.1 KB)
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Albireo: An Interactive Tool for Visually Summarizing Computational Notebook Structure. In: 2019 Symposium on Visualization in Data Science (VDS’19). 2019 Symposium on Visualization in Data Science (VDS’19). ; 2019. p. .
Albireo__Visualizing_Computational_Notebooks.pdf (984.33 KB)
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DeepVA: Bridging Cognition and Computation through Semantic Interaction and Deep Learning. In: Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS’19. . Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS’19. . ; 2019. p. .
MLUI_2019-2.pdf (8.51 MB)
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Dropping the Baton?: Understanding Errors and Bottlenecks in a Crowdsourced Sensemaking Pipeline. Proc. ACM Hum.-Comput. Interact. [Internet]. 2019;3:136:1–136:26. Available from: http://doi.acm.org/10.1145/3359238
cscw136-li.pdf (2.09 MB)
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The Effect of Edge Bundling and Seriation on Sensemaking of Biclusters in Bipartite Graphs. IEEE Transactions on Visualization and Computer Graphics. 2019;25(10):2983-2998.
08423100.pdf (5.86 MB)
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Evaluating Semantic Interaction on Word Embeddings via Simulation. In: EValuation of Interactive VisuAl Machine Learning systems, an IEEE VIS 2019 Workshop. EValuation of Interactive VisuAl Machine Learning systems, an IEEE VIS 2019 Workshop. ; 2019. p. .
sub1013.pdf (786.6 KB)
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Immersive Analytics: Theory and Research Agenda. Frontiers in Robotics and AI [Internet]. 2019;6:82. Available from: https://www.frontiersin.org/article/10.3389/frobt.2019.00082
92e73d798fc9ef4c3da4c542606c9a38f337.pdf (2.79 MB)
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Intelligent Systems for Geosciences: An Essential Research Agenda. COMMUNICATIONS OF THE ACM. 2019;62(1):76-84.
CACM-IS-GEO-2018.pdf (3.02 MB)
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Interactive Bicluster Aggregation in Bipartite Graphs. In: VIS 2019 Short Papers. VIS 2019 Short Papers. ; 2019. p. .
. Interactive Visual Analytics for Sensemaking with Big Text. Big Data Research [Internet]. 2019;16:49 - 58. Available from: http://www.sciencedirect.com/science/article/pii/S2214579618302995
1-s2.0-S2214579618302995-main.pdf (1.32 MB)
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Machine Learning from Interaction in Multi-Model Visual Analytics. In: Proceedings of the ACM CHI Conference Workshop on Human-Centered Machine Learning Perspectives at CHI’19. Proceedings of the ACM CHI Conference Workshop on Human-Centered Machine Learning Perspectives at CHI’19. ; 2019. p. .
HCML_Submission.pdf (552.21 KB)
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Machine Learning from User Interaction for Visualization and Analytics: A Workshop-Generated Research Agenda. In: Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS’19. Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS’19. ; 2019. p. .
MLUI_Long_Paper.pdf (5.22 MB)
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Pollux: Interactive Cluster-First Projections of High-Dimensional Data. In: 2019 Symposium on Visualization in Data Science (VDS’19). 2019 Symposium on Visualization in Data Science (VDS’19). ; 2019. p. .
The_Pollux_Paper-2.pdf (1.8 MB)
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Simultaneous Interaction with Dimension Reduction and Clustering Projections. In: Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion. Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion. New York, NY, USA; 2019. p. 89–90. Available from: http://doi.acm.org/10.1145/3308557.3308718
p89-wenskovitch.pdf (478.5 KB)
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Towards insight-driven sampling for big data visualisation. Behaviour & Information Technology [Internet]. 2019:1-20. Available from: https://doi.org/10.1080/0144929X.2019.1616223
Towards insight driven sampling for big data visualisation.pdf (2.84 MB)
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Uncertainty in Interactive WMDS Visualizations. 2019 Symposium on Visualization in Data Science Posters. 2019.
uncertainty-in-wmds-vds.pdf (355.18 KB)
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Be the Data: Embodied Visual Analytics. IEEE Transactions on Learning Technologies. 2018;11(1):81-95.
data-embodied-visual.pdf (6.31 MB)
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A Bidirectional Pipeline for Semantic Interaction. In: VIS Workshop on Machine Learning from User Interaction for Visualization and Analytics. VIS Workshop on Machine Learning from User Interaction for Visualization and Analytics. ; 2018. p. .
Pipeline.pdf (5.02 MB)
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The Cognitive and Computational Benefits and Limitations of Clustering for Sensemaking. In: CHI '18 Workshop on Sensemaking in a Senseless World. CHI '18 Workshop on Sensemaking in a Senseless World. Montreal, QC, Canada; 2018. p. .
cognitive-computational-benefits.pdf (374.93 KB)
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Construction and Usage of the Semantic Interaction Pipeline. 2018:1-29.
construction-usage-semantic.pdf (4.5 MB)
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CrowdIA: Solving Mysteries with Crowdsourced Sensemaking. Proc. ACM Hum.-Comput. Interact. [Internet]. 2018;2. Available from: https://doi.org/10.1145/3274374
cscw105-liA.pdf (7.93 MB)
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