Stephan Günnemann - Google Scholar

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	All	Since 2015
Citations	2957	2302
h-index	30	27
i10-index	55	44

620

310

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465

2009201020112012201320142015201620172018201920208 56 74 142 184 174 223 260 280 375 602 555

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Thomas SeidlProfessor of Computer Science, Ludwig-Maximilians-Universität München (LMU Munich), GermanyVerified email at dbs.ifi.lmu.de
Emmanuel MüllerProfessor of Computer Science, Bonn-Aachen International Center for Information TechnologyVerified email at bit.uni-bonn.de
Aleksandar BojchevskiTechnical University of MunichVerified email at in.tum.de
Ines FärberData Management and Data ExplorationVerified email at cs.rwth-aachen.de
Christos FaloutsosCMUVerified email at cs.cmu.edu
Daniel ZügnerTechnical University of MunichVerified email at in.tum.de
Hardy KremerDeloitte Analytics Institute, GermanyVerified email at deloitte.de
Oleksandr ShchurPhD student, Technical University of MunichVerified email at in.tum.de
Thomas NeumannProfessor, Technische Universität MünchenVerified email at in.tum.de
Johannes KlicperaTechnical University of MunichVerified email at in.tum.de
Danai KoutraUniversity of Michigan, Ann ArborVerified email at umich.edu
Mohit KumarUdaan, Flipkart, Accenture Technology Labs, Carnegie Mellon UniversityVerified email at udaan.com
Miguel AraujoFeedzaiVerified email at feedzai.com
Manuel ThenTechnische Universität MünchenVerified email at manuel-then.de
Neil ShahSenior Research Scientist, Snap Inc.Verified email at snap.com
Alex BeutelStaff Research Scientist, GoogleVerified email at google.com
Leman AkogluAssociate Professor of Information Systems, Heinz College, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Bryan HooiNational University of SingaporeVerified email at comp.nus.edu.sg
Nikou GünnemannResearch Scientist, SiemensVerified email at tum.de
Evangelos E. PapalexakisAssistant Professor, University of California RiversideVerified email at cs.ucr.edu

Stephan Günnemann

Professor of Computer Science, Technical University of Munich

Verified email at in.tum.de - Homepage

Machine Learning Data Mining Graphs Robustness


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Evaluating clustering in subspace projections of high dimensional data E Müller, S Günnemann, I Assent, T Seidl Proceedings of the VLDB Endowment 2 (1), 1270-1281, 2009	303	2009
Adversarial attacks on neural networks for graph data D Zügner, A Akbarnejad, S Günnemann Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	161	2018
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking A Bojchevski, S Günnemann International Conference on Learning Representations (ICLR), 2018	136*	2018
On using class-labels in evaluation of clusterings I Färber, S Günnemann, HP Kriegel, P Kröger, E Müller, E Schubert, ... MultiClust: 1st international workshop on discovering, summarizing and using …, 2010	119	2010
Subspace clustering meets dense subgraph mining: A synthesis of two paradigms S Gunnemann, I Farber, B Boden, T Seidl 2010 IEEE International Conference on Data Mining, 845-850, 2010	117	2010
Netgan: Generating graphs via random walks A Bojchevski, O Shchur, D Zügner, S Günnemann ICML 2018, 2018	110	2018
Mining coherent subgraphs in multi-layer graphs with edge labels B Boden, S Günnemann, H Hoffmann, T Seidl Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012	109	2012
Com2: fast automatic discovery of temporal (‘comet’) communities M Araujo, S Papadimitriou, S Günnemann, C Faloutsos, P Basu, A Swami, ... Pacific-Asia Conference on Knowledge Discovery and Data Mining, 271-283, 2014	86	2014
Relevant subspace clustering: Mining the most interesting non-redundant concepts in high dimensional data E Müller, I Assent, S Günnemann, R Krieger, T Seidl 2009 Ninth IEEE International Conference on Data Mining, 377-386, 2009	84	2009
Birdnest: Bayesian inference for ratings-fraud detection B Hooi, N Shah, A Beutel, S Günnemann, L Akoglu, M Kumar, D Makhija, ... Proceedings of the 2016 SIAM International Conference on Data Mining, 495-503, 2016	81	2016
Pitfalls of graph neural network evaluation O Shchur, M Mumme, A Bojchevski, S Günnemann arXiv preprint arXiv:1811.05868, 2018	76	2018
Discovering multiple clustering solutions: Grouping objects in different views of the data E Muller, S Gunnemann, I Farber, T Seidl 2012 IEEE 28th International Conference on Data Engineering, 1207-1210, 2012	70	2012
Predict then propagate: Graph neural networks meet personalized pagerank J Klicpera, A Bojchevski, S Günnemann arXiv preprint arXiv:1810.05997, 2018	68*	2018
Adversarial attacks on graph neural networks via meta learning D Zügner, S Günnemann arXiv preprint arXiv:1902.08412, 2019	61	2019
DB-CSC: a density-based approach for subspace clustering in graphs with feature vectors S Günnemann, B Boden, T Seidl Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011	61	2011
Detecting anomalies in dynamic rating data: A robust probabilistic model for rating evolution S Günnemann, N Günnemann, C Faloutsos Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014	56	2014
Introduction to tensor decompositions and their applications in machine learning S Rabanser, O Shchur, S Günnemann arXiv preprint arXiv:1711.10781, 2017	52	2017
External evaluation measures for subspace clustering S Günnemann, I Färber, E Müller, I Assent, T Seidl Proceedings of the 20th ACM international conference on Information and …, 2011	51	2011
Spectral subspace clustering for graphs with feature vectors S Günnemann, I Färber, S Raubach, T Seidl 2013 IEEE 13th International Conference on Data Mining, 231-240, 2013	49	2013
Adversarial attacks on node embeddings via graph poisoning A Bojchevski, S Günnemann International Conference on Machine Learning, 695-704, 2019	48*	2019

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