Matthias Hein

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Francesco CroceEPFLVerified email at cs.uni-saarland.de
Bernt SchieleProfessor, Max Planck Institute for Informatics, Saarland University, Saarland Informatics CampusVerified email at mpi-inf.mpg.de
Maksym AndriushchenkoPostdoctoral Researcher at EPFLVerified email at epfl.ch
Ulrike von LuxburgUniversity of TübingenVerified email at informatik.uni-tuebingen.de
Quynh NguyenSenior Research ScientistVerified email at quynhnguyen.org
Francesco TudiscoThe University of EdinburghVerified email at ed.ac.uk
Julian BitterwolfPhD Student, University of TübingenVerified email at uni-tuebingen.de
David StutzResearch Scientist, DeepMindVerified email at deepmind.com
Anna KhorevaHead of Applied Science at ZalandoVerified email at zalando.de
Nicolas FlammarionEPFLVerified email at epfl.ch
Antoine GautierQuantPiVerified email at quantpi.com
Max LapinResearcher, Stability AIVerified email at stability.ai
Maximilian AugustinPhD Student, University of TuebingenVerified email at uni-tuebingen.de
Thomas BühlerAviraVerified email at avira.com
Olivier BousquetGoogleVerified email at m4x.org
Rodrigo BenensonResearch scientist at GoogleVerified email at google.com
Philipp HennigUniversity of TübingenVerified email at uni-tuebingen.de
Simon SetzerSaarland UniversityVerified email at mia.uni-saarland.de
Syama Sundar RangapuramAmazonVerified email at amazon.de
Agustinus KristiadiPostdoc, Vector InstituteVerified email at vectorinstitute.ai

Matthias Hein

Professor of Computer Science, University of Tübingen

Verified email at uni-tuebingen.de - Homepage

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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	1996	2020
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	1095	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	958	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	869	2016
Robustbench: a standardized adversarial robustness benchmark F Croce, M Andriushchenko, V Sehwag, E Debenedetti, N Flammarion, ... arXiv preprint arXiv:2010.09670, 2020	762	2020
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	653	2019
Formal guarantees on the robustness of a classifier against adversarial manipulation M Hein, M Andriushchenko NIPS 2017, 2017	634	2017
Minimally distorted adversarial examples with a fast adaptive boundary attack F Croce, M Hein International Conference on Machine Learning, 2196-2205, 2020	552	2020
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	409	2005
Spectral clustering based on the graph p-Laplacian T Bühler, M Hein Proceedings of the 26th annual international conference on machine learning …, 2009	386	2009
Variants of rmsprop and adagrad with logarithmic regret bounds MC Mukkamala, M Hein International conference on machine learning, 2545-2553, 2017	362	2017
Graph laplacians and their convergence on random neighborhood graphs. M Hein, JY Audibert, U Luxburg Journal of Machine Learning Research 8 (6), 2007	352	2007
Being bayesian, even just a bit, fixes overconfidence in relu networks A Kristiadi, M Hein, P Hennig International conference on machine learning, 5436-5446, 2020	327	2020
Disentangling adversarial robustness and generalization D Stutz, M Hein, B Schiele Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	325	2019
The loss surface of deep and wide neural networks Q Nguyen, M Hein International conference on machine learning, 2603-2612, 2017	322	2017
Provably robust boosted decision stumps and trees against adversarial attacks M Andriushchenko, M Hein Advances in neural information processing systems 32, 2019	299	2019
Intrinsic dimensionality estimation of submanifolds in R^d M Hein, JY Audibert Proceedings of the 22nd international conference on Machine learning, 289-296, 2005	297	2005
Manifold denoising M Hein, M Maier Advances in neural information processing systems 19, 2006	257	2006
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	250	2010
Sparse and imperceivable adversarial attacks F Croce, M Hein Proceedings of the IEEE/CVF international conference on computer vision …, 2019	242	2019

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