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ORCIDMichaël Aupetit 0001
Michaël J. Aupetit
Person information
- affiliation: Hamad Bin Khalifa University, Qatar Computing Research Institute, Doha, Qatar
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2020 – today
- 2024
[j26]Mostafa M. Hamza, Ehsan Ullah, Abdelkader Baggag, Halima Bensmail, Michael Sedlmair, Michaël Aupetit
:
ClustML: A measure of cluster pattern complexity in scatterplots learnt from human-labeled groupings. Inf. Vis. 23(2): 105-122 (2024)- [j25]Hyeon Jeon, Yun-Hsin Kuo, Michaël Aupetit, Kwan-Liu Ma, Jinwook Seo:
: Improving Label-Based Evaluation of Dimensionality Reduction. IEEE Trans. Vis. Comput. Graph. 30(1): 781-791 (2024) - 2023
- [d1]Mostafa M. Abbas, Ehsan Ullah, Abdelkader Baggag, Halima Bensmail, Michael Sedlmair, Michaël Aupetit:
Datasets and code for ClustMe and ClustML visual quality measures of grouping patterns in monochrome scatterplots. Zenodo, 2023
- [i14]Hyeon Jeon, Yun-Hsin Kuo, Michaël Aupetit, Kwan-Liu Ma, Jinwook Seo:
Classes are not Clusters: Improving Label-based Evaluation of Dimensionality Reduction. CoRR abs/2308.00278 (2023) - 2022
- [c42]Sorina Mustatea, Michaël Aupetit, Jaakko Peltonen, Sylvain Lespinats, Denys Dutykh:
Supervised dimensionality reduction technique accounting for soft classes. ESANN 2022 - [c41]Ala Abuthawabeh, Abdelkader Baggag, Michaël Aupetit:
Augmented Intelligence with Interactive Voronoi Treemap for Scalable Grouping: a Usage Scenario with Wearable Data. EuroVis (Short Papers) 2022: 43-47 - [i13]Hyeon Jeon, Michaël J. Aupetit, Soohyun Lee, Hyung-Kwon Ko, Youngtaek Kim, Jinwook Seo:
Distortion-Aware Brushing for Interactive Cluster Analysis in Multidimensional Projections. CoRR abs/2201.06379 (2022) - [i12]Michaël Aupetit, Ahmed Ali:
ClassSPLOM - A Scatterplot Matrix to Visualize Separation of Multiclass Multidimensional Data. CoRR abs/2201.12822 (2022) - [i11]Hyeon Jeon, Michaël Aupetit, DongHwa Shin, Aeri Cho, Seokhyeon Park, Jinwook Seo:
Sanity Check for External Clustering Validation Benchmarks using Internal Validation Measures. CoRR abs/2209.10042 (2022) - 2021
- [j24]Talar Boghos Yacoubian, Dena Ahmed S. Al Thani, Michaël Aupetit:
The Role of a Facilitator in Co-Design Applications for Exploratory Analysis in Domains of High Complexity: The Case of MAHiCGO. IEEE Access 9: 38296-38317 (2021) - [j23]Fabrice Mayran de Chamisso, Daniela Cancila, Laurent Soulier, Roberto Passerone, Michaël Aupetit:
Lifelong Exploratory Navigation: An Architecture for Safer Mobile Robots. IEEE Des. Test 38(5): 57-64 (2021) - [c40]Ala Abuthawabeh, Michaël Aupetit:
Toward an Interactive Voronoi Treemap for Manual Arrangement and Grouping. EuroVis (Short Papers) 2021: 97-101 - [i10]Michaël Aupetit:
Aquanims: Area-Preserving Animated Transitions in Statistical Data Graphics based on a Hydraulic Metaphor. CoRR abs/2101.12511 (2021) - [i9]Mostafa M. Abbas, Ehsan Ullah, Abdelkader Baggag, Halima Bensmail, Michael Sedlmair, Michaël Aupetit:
ClustRank: a Visual Quality Measure Trained on Perceptual Data for Sorting Scatterplots by Cluster Patterns. CoRR abs/2106.00599 (2021) - 2020
- [j22]Ignacio Perez-Pozuelo, Bing Zhai, João R. M. Palotti, Raghvendra Mall, Michaël Aupetit, Juan M. Garcia-Gomez, Shahrad Taheri, Yu Guan, Luis Fernández-Luque:
The future of sleep health: a data-driven revolution in sleep science and medicine. npj Digit. Medicine 3 (2020) - [c39]René Cutura, Michaël Aupetit, Jean-Daniel Fekete, Michael Sedlmair:
Comparing and Exploring High-Dimensional Data with Dimensionality Reduction Algorithms and Matrix Visualizations. AVI 2020: 10:1-10:9 - [c38]Kareem Darwish, Peter Stefanov, Michaël J. Aupetit, Preslav Nakov:
Unsupervised User Stance Detection on Twitter. ICWSM 2020: 141-152 - [c37]Benoît Colange, Jaakko Peltonen, Michaël Aupetit, Denys Dutykh, Sylvain Lespinats:
Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction. NeurIPS 2020 - [c36]Ala Abuthawabeh, Michaël Aupetit:
A Force-Directed Power Diagram Approach for Interactive Voronoi Treemaps. EuroVis (Short Papers) 2020: 109-113 - [i8]Michaël Aupetit:
Aquanims - Area-Preserving Animated Transitions based on a Hydraulic Metaphor. CoRR abs/2011.07532 (2020) - [i7]Ali Sheharyar, Talar Boghos Yacoubian, Dina Aljogol, Borbala Mifsud, Dena Al-Thani, Michaël Aupetit:
An Enhanced MA Plot with R-Shiny to Ease Exploratory Analysis of Transcriptomic Data. CoRR abs/2012.04411 (2020)
2010 – 2019
- 2019
- [j21]Ehsan Ullah, Michaël Aupetit, Arun Das, Abhishek Patil, Nooral Al Muftah, Reda Rawi, Mohamad Saad, Halima Bensmail:
KinVis: a visualization tool to detect cryptic relatedness in genetic datasets. Bioinform. 35(15): 2683-2685 (2019) - [j20]Mostafa M. Abbas, Michaël Aupetit, Michael Sedlmair, Halima Bensmail:
ClustMe: A Visual Quality Measure for Ranking Monochrome Scatterplots based on Cluster Patterns. Comput. Graph. Forum 38(3): 225-236 (2019) - [j19]João R. M. Palotti, Raghvendra Mall, Michaël Aupetit, Michael Rueschman, Meghna Singh, Aarti Sathyanarayana, Shahrad Taheri, Luis Fernández-Luque:
Benchmark on a large cohort for sleep-wake classification with machine learning techniques. npj Digit. Medicine 2 (2019) - [j18]Luis Gustavo Nonato, Michaël Aupetit:
Multidimensional Projection for Visual Analytics: Linking Techniques with Distortions, Tasks, and Layout Enrichment. IEEE Trans. Vis. Comput. Graph. 25(8): 2650-2673 (2019) - [c35]Luana Micallef, Hans-Jörg Schulz, Marco Angelini, Michaël Aupetit, Remco Chang, Jörn Kohlhammer, Adam Perer, Giuseppe Santucci:
The Human User in Progressive Visual Analytics. EuroVis (Short Papers) 2019: 19-23 - [c34]Michaël Aupetit, Michael Sedlmair, Mostafa M. Abbas, Abdelkader Baggag, Halima Bensmail:
Toward Perception-Based Evaluation of Clustering Techniques for Visual Analytics. IEEE VIS (Short Papers) 2019: 141-145 - [i6]Kareem Darwish, Peter Stefanov, Michaël J. Aupetit, Preslav Nakov:
Unsupervised User Stance Detection on Twitter. CoRR abs/1904.02000 (2019) - 2018
- [c33]Matheus Araújo, Yelena Mejova, Michaël Aupetit, Ingmar Weber:
Visualizing Geo-Demographic Urban Data. CSCW Companion 2018: 45-48 - [c32]René Cutura, Stefan Holzer, Michaël Aupetit, Michael Sedlmair:
VisCoDeR: A tool for visually comparing dimensionality reduction algorithms. ESANN 2018 - [c31]Firoj Alam, Ferda Ofli, Muhammad Imran, Michaël Aupetit:
A Twitter Tale of Three Hurricanes: Harvey, Irma, and Maria. ISCRAM 2018 - [i5]Firoj Alam, Ferda Ofli, Muhammad Imran, Michaël Aupetit:
A Twitter Tale of Three Hurricanes: Harvey, Irma, and Maria. CoRR abs/1805.05144 (2018) - 2017
- [j17]Luis Fernández-Luque, Meghna Singh, Ferda Ofli, Yelena Mejova, Ingmar Weber, Michaël Aupetit, Sahar Karim Jreige, Ahmed K. Elmagarmid, Jaideep Srivastava, Mohamed Ahmedna:
Implementing 360° Quantified Self for childhood obesity: feasibility study and experiences from a weight loss camp in Qatar. BMC Medical Informatics Decis. Mak. 17(1): 37:1-37:13 (2017) - [j16]Luis Fernández-Luque, Meghna Singh, Ferda Ofli, Yelena Mejova, Ingmar Weber, Michaël Aupetit, Sahar Karim Jreige, Ahmed K. Elmagarmid, Jaideep Srivastava, Mohamed Ahmedna:
Erratum to: Implementing 360° Quantified Self for childhood obesity: feasibility study and experiences from a weight loss camp in Qatar. BMC Medical Informatics Decis. Mak. 17(1): 62:1-62:2 (2017) - [c30]Michaël Aupetit, Luis Fernández-Luque, Meghna Singh, Jaideep Srivastava:
Visualization of Wearable Data and Biometrics for Analysis and Recommendations in Childhood Obesity. CBMS 2017: 678-679 - [c29]Matheus Lima Diniz Araújo, Yelena Mejova, Michaël Aupetit, Ingmar Weber:
Visualizing Health Awareness in the Middle East. ICWSM 2017: 725-726 - [c28]Michaël Aupetit, Muhammad Imran:
Interactive Monitoring of Critical Situational Information on Social Media. ISCRAM 2017 - [i4]Michaël Aupetit, Luis Fernández-Luque, Meghna Singh, Jaideep Srivastava:
Visualization of Wearable Data and Biometrics for Analysis and Recommendations in Childhood Obesity. CoRR abs/1705.03691 (2017) - [i3]Nicolas Heulot, Jean-Daniel Fekete, Michaël Aupetit:
Visualizing Dimensionality Reduction Artifacts: An Evaluation. CoRR abs/1705.05283 (2017) - 2016
- [j15]Reda Rawi, Raghvendra Mall, Khalid Kunji, Mohammed El Anbari, Michaël Aupetit, Ehsan Ullah, Halima Bensmail:
COUSCOus: improved protein contact prediction using an empirical Bayes covariance estimator. BMC Bioinform. 17: 533:1-533:9 (2016) - [c27]Michaël Aupetit, Michael Sedlmair:
SepMe: 2002 New visual separation measures. PacificVis 2016: 1-8 - [c26]Michaël Aupetit, Ehsan Ullah, Reda Rawi, Halima Bensmail:
A design study to identify inconsistencies in kinship information: The case of the 1000 Genomes project. PacificVis 2016: 254-258 - [c25]Michaël Aupetit, Yury Zhauniarovich, Giorgos Vasiliadis, Marc Dacier, Yazan Boshmaf:
Visualization of actionable knowledge to mitigate DRDoS attacks. VizSEC 2016: 1-8 - 2015
- [j14]Michael Sedlmair, Michaël Aupetit:
Data-driven Evaluation of Visual Quality Measures. Comput. Graph. Forum 34(3): 201-210 (2015) - [j13]Michaël Aupetit, Laurens van der Maaten:
Introduction to the special issue on visual analytics using multidimensional projections. Neurocomputing 150: 543-545 (2015) - [j12]Sylvain Lespinats, Michaël Aupetit, Anke Meyer-Baese:
ClassiMap: A New Dimension Reduction Technique for Exploratory Data Analysis of Labeled Data. Int. J. Pattern Recognit. Artif. Intell. 29(6): 1551008:1-1551008:45 (2015) - [c24]Fabrice Mayran de Chamisso, Laurent Soulier, Michaël Aupetit:
Exploratory Digraph Navigation Using A. IJCAI 2015: 1624-1630 - 2014
- [c23]Michaël Aupetit:
Sanity check for class-coloring-based evaluation of dimension reduction techniques. BELIV 2014: 134-141 - [c22]Michaël Aupetit, Nicolas Heulot, Jean-Daniel Fekete:
A multidimensional brush for scatterplot data analytics. IEEE VAST 2014: 221-222 - [c21]Ricardo de Aldama, Michaël Aupetit:
Interpretability in Fuzzy Systems Optimization: A Topological Approach. IPMU (1) 2014: 588-597 - 2013
- [c20]Khrystyna Kyrgyzova, Lorène Allano, Michaël Aupetit:
Alternating Optimization for Lambertian Photometric Stereo Model with Unknown Lighting Directions. CAIP (2) 2013: 354-361 - [c19]Maxime Maillot, Michaël Aupetit, Gérard Govaert:
Extraction des nombres de Betti avec un modèle génératif. EGC 2013: 97-102 - [c18]Nicolas Heulot, Michaël Aupetit, Jean-Daniel Fekete:
ProxiLens: Interactive Exploration of High-Dimensional Data using Projections. VAMP@EuroVis 2013 - [c17]Sylvain Lespinats, Michaël Aupetit:
ClassiMap: a Supervised Mapping Technique for Decision Support. VAMP@EuroVis 2013 - [e1]Michaël Aupetit, Laurens van der Maaten:
1st International Workshop on Visual Analytics Using Multidimensional Projections, VAMP@EuroVis 2013, Leipzig, Germany, June 19, 2013. Eurographics Association 2013, ISBN 978-3-905674-53-8 [contents] - 2012
- [b1]Michaël Aupetit:
Approches topologiques pour l'analyse exploratoire de données et l'aide à la décision. (Topological approaches for data analytic and decision support). University of Paris-Sud, France, 2012 - [c16]Maxime Maillot, Michaël Aupetit, Gérard Govaert:
A generative model that learns Betti numbers from a data set. ESANN 2012 - [i2]Sylvain Lespinats, Anke Meyer-Bäse, Michaël Aupetit:
A new supervised non-linear mapping. CoRR abs/1203.2021 (2012) - 2011
- [j11]Sylvain Lespinats, Michaël Aupetit:
CheckViz: Sanity Check and Topological Clues for Linear and Non-Linear Mappings. Comput. Graph. Forum 30(1): 113-125 (2011) - 2010
- [j10]Pierre Gaillard, Michaël Aupetit, Gérard Govaert:
Un graphe génératif pour la classification semi-supervisée. Ingénierie des Systèmes d Inf. 15(2): 97-119 (2010) - [c15]Sylvain Lespinats, Michaël Aupetit:
Mapping without visualizing local default is nonsense. ESANN 2010 - [c14]Axel Wismüller, Michel Verleysen, Michaël Aupetit, John Aldo Lee:
Recent Advances in Nonlinear Dimensionality Reduction, Manifold and Topological Learning. ESANN 2010 - [c13]Michaël Aupetit, Lorène Allano, Isabelle Espagnon, Guillaume Sannie:
Visual Analytics to Check Marine Containers in the Eritr\@c Project. EuroVAST@EuroVis 2010
2000 – 2009
- 2009
- [j9]Michaël Aupetit:
Nearly homogeneous multi-partitioning with a deterministic generator. Neurocomputing 72(7-9): 1379-1389 (2009) - [j8]Pierre Gaillard, Michaël Aupetit, Gérard Govaert:
Le Graphe Génératif Gaussien. Monde des Util. Anal. Données 40: 103-120 (2009) - 2008
- [j7]Pierre Gaillard, Michaël Aupetit, Gérard Govaert:
Learning topology of a labeled data set with the supervised generative Gaussian graph. Neurocomputing 71(7-9): 1283-1299 (2008) - [j6]Michaël Aupetit, Pierre Gaillard:
Mesurer et visualiser les distorsions dans les techniques de projection continues. Rev. d'Intelligence Artif. 22(3-4): 443-472 (2008) - [c12]Michaël Aupetit, Pierre Gaillard, Gérard Govaert:
Un modèle génératif pour l'Apprentissage de la Topologie. AAFD 2008: 49-76 - [c11]Michaël Aupetit:
Homogeneous bipartition based on multidimensional ranking. ESANN 2008: 259-264 - 2007
- [j5]Michaël Aupetit:
Visualizing distortions and recovering topology in continuous projection techniques. Neurocomputing 70(7-9): 1304-1330 (2007) - [j4]Dominique Lepetz, Max Némoz-Gaillard, Michaël Aupetit:
Concerning the differentiability of the energy function in vector quantization algorithms. Neural Networks 20(5): 621-630 (2007) - [c10]Pierre Gaillard, Michaël Aupetit, Gérard Govaert:
Learning topology of a labeled data set with the supervised generative gaussian graph. ESANN 2007: 235-240 - [c9]Pierre Gaillard, Michaël Aupetit, Gérard Govaert:
Apprentissage statistique de la topologie d'un ensemble de données étiquetées. EGC 2007: 455-460 - 2006
- [j3]David Mercier, Pierre Gaillard, Michaël Aupetit, Carole Maillard, Robert Quach, Jean-Denis Muller:
How to help seismic analysts to verify the French seismic bulletin? Eng. Appl. Artif. Intell. 19(7): 797-806 (2006) - [c8]Michaël Aupetit:
Visualizing the trustworthiness of a projection. ESANN 2006: 271-276 - [i1]Dominique Lepetz, Max Némoz-Gaillard, Michaël Aupetit:
Concerning the differentiability of the energy function in vector quantization algorithms. CoRR abs/cs/0604046 (2006) - 2005
- [j2]Michaël Aupetit, Thibaud Catz:
High-dimensional labeled data analysis with topology representing graphs. Neurocomputing 63: 139-169 (2005) - [c7]Michaël Aupetit:
Learning Topology with the Generative Gaussian Graph and the EM Algorithm. NIPS 2005: 83-90 - 2004
- [c6]Michaël Aupetit:
Visualizing distortions in continuous projection techniques. ESANN 2004: 465-470 - 2003
- [c5]Michaël Aupetit:
High-dimensional labeled data analysis with Gabriel graphs. ESANN 2003: 21-26 - [c4]Michaël Aupetit:
Robust Topology Representing Networks. ESANN 2003: 45-50 - 2002
- [j1]Michaël Aupetit, Pierre Couturier, Pierre Massotte:
gamma-Observable neighbours for vector quantization. Neural Networks 15(8-9): 1017-1027 (2002) - 2001
- [c3]Michaël Aupetit, Pierre Couturier, Pierre Massotte:
Induced Voronoï Kernels for Principal Manifolds Approximation. WSOM 2001: 73-80 - [c2]Michaël Aupetit, Pierre Couturier, Pierre Massotte:
Vector Quantization with γ-Observable Neighbors. WSOM 2001: 230-237 - 2000
- [c1]Michaël Aupetit, Pierre Couturier, Pierre Massotte:
A 'Recruiting Neural-Gas' for Function Approximation. IJCNN (3) 2000: 91-96
Coauthor Index
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