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Mike Sips
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- affiliation: Stanford University, USA
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2020 – today
- 2024
- [c23]Yulia Grushetskaya, Mike Sips, Reyko Schachtschneider, Mohammadmehdi Saberioon, Akram Mahan:
HPExplorer: XAI Method to Explore the Relationship Between Hyperparameters and Model Performance. ECML/PKDD (9) 2024: 319-334 - [i2]Tobias Rawald, Mike Sips, Norbert Marwan:
PyRQA - Conducting Recurrence Quantification Analysis on Very Long Time Series Efficiently. CoRR abs/2402.16853 (2024) - 2023
- [j16]Doris Dransch, Daniel Eggert
, Mike Sips:
F4ESS - a framework for interdisciplinary data-driven earth system science. Int. J. Digit. Earth 16(1): 3973-3986 (2023) - [c22]Mike Sips, Magdalena Vassileva, Daniel Eggert, Mahdi Motagh:
MultiSat4Slows System for Detecting and Assessing Potentially Active Landslide Regions - Initial Results from an Ongoing Interdisciplinary Collaboration. EnvirVis@EuroVis 2023: 85-91 - 2022
- [j15]Daniel Eggert
DASF: A data analytics software framework for distributed environments. J. Open Source Softw. 7(78): 4052 (2022)
2010 – 2019
- 2018
- [j14]Andrea Unger, Nadine Drager
Understanding a Sequence of Sequences: Visual Exploration of Categorical States in Lake Sediment Cores. IEEE Trans. Vis. Comput. Graph. 24(1): 66-76 (2018) - [r2]Mike Sips:
Visual Clustering. Encyclopedia of Database Systems (2nd ed.) 2018 - 2017
- [j13]Tobias Rawald, Mike Sips, Norbert Marwan:
PyRQA - Conducting recurrence quantification analysis on very long time series efficiently. Comput. Geosci. 104: 101-108 (2017) - 2016
- [j12]Mike Sips
Toward a Visual Analytics Approach to Support Multi-Sensor Analysis in Remote Sensing Science. Datenbank-Spektrum 16(3): 219-225 (2016) - [c21]Daniel Eggert, Mike Sips, Patrick Köthur:
Towards Visual Analytics for Multi-Sensor Analysis of Remote Sensing Archives. EnvirVis@EuroVis 2016: 7-11 - [c20]Patrick Köthur, Daniel Eggert, Andreas Schenk, Mike Sips:
Visual Analytics for Persistent Scatterer Interferometry: First Steps and Future Challenges. EuroVA@EuroVis 2016: 37-41 - 2015
- [j11]Patrick Köthur, Carl Witt, Mike Sips
Visual Analytics for Correlation-Based Comparison of Time Series Ensembles. Comput. Graph. Forum 34(3): 411-420 (2015) - [c19]Tobias Rawald, Mike Sips, Norbert Marwan, Ulf Leser:
Massively Parallel Analysis of Similarity Matrices on Heterogeneous Hardware. EDBT/ICDT Workshops 2015: 56-62 - [c18]Janis Jatnieks, Mike Sips, Marco De Lucia, Doris Dransch:
Towards Interactive Definition of Fast Surrogate Models for Geochemical Simulations Using Visual Analysis. EnvirVis@EuroVis 2015: 31-35 - 2014
- [j10]Patrick Köthur, Mike Sips
Interactive visual summaries for detection and assessment of spatiotemporal patterns in geospatial time series. Inf. Vis. 13(3): 283-298 (2014) - [j9]Patrick Köthur, Mike Sips
Visual Analytics for Comparison of Ocean Model Output with Reference Data: Detecting and Analyzing Geophysical Processes Using Clustering Ensembles. IEEE Trans. Vis. Comput. Graph. 20(12): 1893-1902 (2014) - [c17]Tobias Rawald, Mike Sips, Ingo Sasgen, Doris Dransch:
An Interactive Visualization Approach to Explore Mass Variations in the Earth System. EnvirVis@EuroVis 2014 - 2013
- [j8]Sungkil Lee
Perceptually Driven Visibility Optimization for Categorical Data Visualization. IEEE Trans. Vis. Comput. Graph. 19(10): 1746-1757 (2013) - 2012
- [j7]Mike Sips
A Visual Analytics Approach to Multiscale Exploration of Environmental Time Series. IEEE Trans. Vis. Comput. Graph. 18(12): 2899-2907 (2012) - [c16]Patrick Köthur, Mike Sips, Julian Kuhlmann, Doris Dransch:
Visualization of Geospatial Time Series from Environmental Modeling Output. EuroVis (Short Papers) 2012 - 2011
- [c15]Axel Radloff, Martin Luboschik, Mike Sips
Supporting Display Scalability by Redundant Mapping. ISVC (1) 2011: 472-483
2000 – 2009
- 2009
- [j6]Mike Sips
Selecting good views of high-dimensional data using class consistency. Comput. Graph. Forum 28(3): 831-838 (2009) - [r1]Mike Sips:
Visual Clustering. Encyclopedia of Database Systems 2009: 3355-3360 - [i1]Mike Sips, Sascha Simon, John Gerth:
Interactive Exploration of the Network Behavior of Personal Machines. Visualization and Monitoring of Network Traffic 2009 - 2007
- [j5]Mike Sips
Highlighting space-time patterns: Effective visual encodings for interactive decision-making. Int. J. Geogr. Inf. Sci. 21(8): 879-893 (2007) - [j4]Jörn Schneidewind, Mike Sips
An automated approach for the optimization of pixel-based visualizations. Inf. Vis. 6(1): 75-88 (2007) - 2006
- [b1]Mike Sips:
Pixel-based visual data mining in large geo-spatial point sets. University of Konstanz, 2006, ISBN 3-86628-048-3, pp. 1-203 - [j3]Christian Panse, Mike Sips
Visualization of Geo-spatial Point Sets via Global Shape Transformation and Local Pixel Placement. IEEE Trans. Vis. Comput. Graph. 12(5): 749-756 (2006) - [c14]Carmen Sanz Merino, Mike Sips
Task-at-hand interface for change detection in stock market data. AVI 2006: 420-427 - [c13]Jörn Schneidewind, Mike Sips
Pixnostics: Towards Measuring the Value of Visualization. IEEE VAST 2006: 199-206 - [c12]Mike Sips
Scalable Pixel-based Visual Interfaces: Challenges and Solutions. IV 2006: 32-38 - [c11]Daniel A. Keim, Jörn Schneidewind, Mike Sips:
Scalable Pixel Based Visual Data Exploration. VIEW 2006: 12-24 - 2005
- [c10]Daniel A. Keim, Florian Mansmann, Christian Panse, Jörn Schneidewind, Mike Sips:
Mail Explorer - Spatial and Temporal Exploration of Electronic Mail. EuroVis 2005: 247-254 - [p1]Daniel A. Keim, Mike Sips
Visual Data-Mining Techniques An earlier version of this paper with focus on visualization techniques and their classification has been published in Visual Data Analysis: An Introduction (D. Hand and M. Berthold, Eds.). The Visualization Handbook 2005: 831-843 - 2004
- [j2]Daniel A. Keim, Christian Panse, Mike Sips
Pixel based visual data mining of geo-spatial data. Comput. Graph. 28(3): 327-344 (2004) - [j1]Daniel A. Keim, Christian Panse, Mike Sips
Visual Data Mining in Large Geospatial Point Sets. IEEE Computer Graphics and Applications 24(5): 36-44 (2004) - [c9]Daniel A. Keim, Jörn Schneidewind, Mike Sips
CircleView: a new approach for visualizing time-related multidimensional data sets. AVI 2004: 179-182 - [c8]Daniel A. Keim, Christian Panse, Jörn Schneidewind, Mike Sips:
Analyzing Large Collections of Email. IKE 2004: 275-281 - [c7]Roland Heilmann, Daniel A. Keim, Christian Panse
RecMap: Rectangular Map Approximations. INFOVIS 2004: 33-40 - [c6]Daniel A. Keim, Helmut Barro, Christian Panse, Jörn Schneidewind, Mike Sips:
Exploring and Visualizing the History of InfoVis. INFOVIS 2004 - [c5]Roland Heilmann, Daniel A. Keim, Christian Panse, Jörn Schneidewind, Mike Sips:
Finding Spatial Patterns in Network Data. PaRMa 2004 - [c4]Daniel A. Keim, Christian Panse, Jörn Schneidewind, Mike Sips:
Geo-Spatial Data Viewer: From Familiar Land-covering to Arbitrary Distorted Geo-Spatial Quadtree Maps. WSCG 2004: 213-220 - 2003
- [c3]Daniel A. Keim, Christian Panse, Mike Sips:
Visual Data Mining of Large Spatial Data Sets. DNIS 2003: 201-215 - [c2]Daniel A. Keim, Christian Panse, Mike Sips, Stephen C. North:
PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets. ICDM 2003: 565-568 - [c1]Daniel A. Keim, Christian Panse, Jörn Schneidewind, Mike Sips, Ming C. Hao, Umeshwar Dayal:
Pushing the Limit in Visual Data Exploration: Techniques and Applications. KI 2003: 37-51
Coauthor Index
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last updated on 2024-09-13 00:44 CEST by the dblp team
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