Matthias Hein

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Bernt SchieleProfessor, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarland UniversityVerified email at mpi-inf.mpg.de
Francesco CroceUniversity of TübingenVerified email at cs.uni-saarland.de
Ulrike von LuxburgUniversity of TübingenVerified email at informatik.uni-tuebingen.de
Maksym AndriushchenkoPhD student at EPFLVerified email at epfl.ch
Quynh NguyenSenior ML ResearcherVerified email at quynhnguyen.org
Francesco TudiscoGran Sasso Science InstituteVerified email at gssi.it
David StutzResearch Scientist, DeepMindVerified email at deepmind.com
Julian BitterwolfPhD Student, University of TübingenVerified email at uni-tuebingen.de
Anna KhorevaResearch Group Leader at Bosch Center for Artificial IntelligenceVerified email at bosch.com
Antoine GautierQuantPiVerified email at quantpi.com
Thomas BühlerAviraVerified email at avira.com
Maksim LapinSenior Applied Scientist, AmazonVerified email at amazon.com
Olivier BousquetGoogleVerified email at m4x.org
Nicolas FlammarionEPFLVerified email at epfl.ch
Rodrigo BenensonResearch scientist at GoogleVerified email at google.com
Simon SetzerSaarland UniversityVerified email at mia.uni-saarland.de
Syama Sundar RangapuramAmazonVerified email at amazon.de
Philipp HennigUniversity of TübingenVerified email at tue.mpg.de
Florian SteinkeProfessor, Energy Information Networks & Systems, TU DarmstadtVerified email at eins.tu-darmstadt.de
Maximilian AugustinPhD Student, University of TuebingenVerified email at uni-tuebingen.de

Matthias Hein

Professor of Computer Science, University of Tübingen

Verified email at uni-tuebingen.de - Homepage

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Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks F Croce, M Hein International conference on machine learning, 2206-2216, 2020	1174	2020
Simple does it: Weakly supervised instance and semantic segmentation A Khoreva, R Benenson, J Hosang, M Hein, B Schiele Proceedings of the IEEE conference on computer vision and pattern …, 2017	779	2017
Latent embeddings for zero-shot classification Y Xian, Z Akata, G Sharma, Q Nguyen, M Hein, B Schiele Proceedings of the IEEE conference on computer vision and pattern …, 2016	770	2016
Square attack: a query-efficient black-box adversarial attack via random search M Andriushchenko, F Croce, N Flammarion, M Hein European conference on computer vision, 484-501, 2020	670	2020
Formal guarantees on the robustness of a classifier against adversarial manipulation M Hein, M Andriushchenko NIPS 2017, 2017	524	2017
Why relu networks yield high-confidence predictions far away from the training data and how to mitigate the problem M Hein, M Andriushchenko, J Bitterwolf Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	459	2019
From graphs to manifolds–weak and strong pointwise consistency of graph Laplacians M Hein, JY Audibert, U Von Luxburg International Conference on Computational Learning Theory, 470-485, 2005	390	2005
Robustbench: a standardized adversarial robustness benchmark F Croce, M Andriushchenko, V Sehwag, E Debenedetti, N Flammarion, ... arXiv preprint arXiv:2010.09670, 2020	365	2020
Spectral clustering based on the graph p-Laplacian T Bühler, M Hein Proceedings of the 26th annual international conference on machine learning …, 2009	361	2009
Minimally distorted adversarial examples with a fast adaptive boundary attack F Croce, M Hein International Conference on Machine Learning, 2196-2205, 2020	348	2020
Graph laplacians and their convergence on random neighborhood graphs. M Hein, JY Audibert, U Luxburg Journal of Machine Learning Research 8 (6), 2007	323	2007
Variants of rmsprop and adagrad with logarithmic regret bounds MC Mukkamala, M Hein International conference on machine learning, 2545-2553, 2017	306	2017
Intrinsic dimensionality estimation of submanifolds in R^d M Hein, JY Audibert Proceedings of the 22nd international conference on Machine learning, 289-296, 2005	283	2005
The loss surface of deep and wide neural networks Q Nguyen, M Hein International conference on machine learning, 2603-2612, 2017	279	2017
Manifold denoising M Hein, M Maier Advances in neural information processing systems 19, 2006	248	2006
Disentangling adversarial robustness and generalization D Stutz, M Hein, B Schiele Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	243	2019
An inverse power method for nonlinear eigenproblems with applications in 1-spectral clustering and sparse PCA M Hein, T Bühler Advances in neural information processing systems 23, 2010	236	2010
Hilbertian metrics and positive definite kernels on probability measures M Hein, O Bousquet International Workshop on Artificial Intelligence and Statistics, 136-143, 2005	224	2005
Influence of graph construction on graph-based clustering measures M Maier, U Luxburg, M Hein Advances in neural information processing systems 21, 2008	217	2008
Non-negative least squares for high-dimensional linear models: Consistency and sparse recovery without regularization M Slawski, M Hein	211	2013

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