Grégoire Montavon

Получаване на мой собствен потребителски профил

Позовавания

	Всички	От 2018
Позовавания	15335	14169
h-индекс	34	32
i10-индекс	49	45

4600

2300

1150

3450

2013201420152016201720182019202020212022202356 79 148 233 540 1046 1804 2732 3640 4507 398

Публичен достъп

Преглед на всички

34 статии

4 статии

налични

неналични

Въз основа на изисквания при финансирането

Съавтори

Klaus-Robert MüllerTU Berlin & Korea University & Google Brain & Max Planck Institute for InformaticsПотвърден имейл адрес: tu-berlin.de
Wojciech SamekProfessor at TU Berlin, Head of AI Department at Fraunhofer HHI, BIFOLD FellowПотвърден имейл адрес: hhi.fraunhofer.de
Alexander BinderAssociate Professor, Singapore Institute of Technology (SIT) and University of Oslo (UiO)Потвърден имейл адрес: singaporetech.edu.sg
Sebastian LapuschkinHead of Explainable AI, Fraunhofer Heinrich Hertz InstituteПотвърден имейл адрес: hhi.fraunhofer.de
Frederick KlauschenInstitute of Pathology, University of Munich (LMU)Потвърден имейл адрес: lmu.de
Leila ArrasResearch Associate, Fraunhofer HHI, GermanyПотвърден имейл адрес: hhi.fraunhofer.de
Jacob KauffmannTU BerlinПотвърден имейл адрес: tu-berlin.de
Matthias RuppLuxembourg Institute of Science and Technology (LIST)Потвърден имейл адрес: list.lu
Christopher J. AndersTechnische Universität BerlinПотвърден имейл адрес: tu-berlin.de
O. Anatole von LilienfeldUniversity of Toronto/Vector Institute/Technical University BerlinПотвърден имейл адрес: utoronto.ca
Kristof T. SchüttPfizerПотвърден имейл адрес: pfizer.com
Lukas RuffAignosticsПотвърден имейл адрес: aignostics.com
Oliver EberleTU BerlinПотвърден имейл адрес: tu-berlin.de
Mikio L. BraunTU Berlin (allumni)Потвърден имейл адрес: getyourguide.de
Thomas SchnakeTechnical University of BerlinПотвърден имейл адрес: tu-berlin.de
Shinichi NakajimaMachine Learning Group, Technische Universität BerlinПотвърден имейл адрес: tu-berlin.de
Jonas LedererPhD student, TU BerlinПотвърден имейл адрес: tu-berlin.de
Maximilian AlberTU BerlinПотвърден имейл адрес: tu-berlin.de
Marco CuturiApple / CREST-ENSAE.Потвърден имейл адрес: apple.com
Simon LetzgusTechnical University of BerlinПотвърден имейл адрес: tu-berlin.de

Следене

Grégoire Montavon

Freie Universität Berlin

Потвърден имейл адрес: fu-berlin.de - Начална страница

Explainable AI Neural Networks Unsupervised Learning


Заглавие Сортиране по цитати Сортиране по година Сортиране по заглавие	Позовавания Позовавания	Година
On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation S Bach, A Binder, G Montavon, F Klauschen, KR Müller, W Samek PloS one 10 (7), e0130140, 2015	3238	2015
Methods for interpreting and understanding deep neural networks G Montavon, W Samek, KR Müller Digital Signal Processing, 2018	2009	2018
Explaining nonlinear classification decisions with deep taylor decomposition G Montavon, S Lapuschkin, A Binder, W Samek, KR Müller Pattern recognition 65, 211-222, 2017	1154	2017
Evaluating the visualization of what a deep neural network has learned W Samek, A Binder, G Montavon, S Lapuschkin, KR Müller IEEE transactions on neural networks and learning systems 28 (11), 2660-2673, 2016	947	2016
Explainable AI: interpreting, explaining and visualizing deep learning W Samek, G Montavon, A Vedaldi, LK Hansen, KR Müller Springer Nature, 2019	777	2019
Unmasking Clever Hans predictors and assessing what machines really learn S Lapuschkin, S Wäldchen, A Binder, G Montavon, W Samek, KR Müller Nature communications 10 (1), 1096, 2019	743	2019
Machine learning of molecular electronic properties in chemical compound space G Montavon, M Rupp, V Gobre, A Vazquez-Mayagoitia, K Hansen, ... New Journal of Physics 15 (9), 095003, 2013	617	2013
Assessment and validation of machine learning methods for predicting molecular atomization energies K Hansen, G Montavon, F Biegler, S Fazli, M Rupp, M Scheffler, ... Journal of Chemical Theory and Computation 9 (8), 3404-3419, 2013	606	2013
Neural networks: tricks of the trade G Montavon, G Orr, KR Müller springer, 2012	563*	2012
Layer-wise relevance propagation: an overview G Montavon, A Binder, S Lapuschkin, W Samek, KR Müller Explainable AI: interpreting, explaining and visualizing deep learning, 193-209, 2019	451	2019
Explaining deep neural networks and beyond: a review of methods and applications W Samek, G Montavon, S Lapuschkin, CJ Anders, KR Müller Proceedings of the IEEE 109 (3), 2021	446*	2021
A unifying review of deep and shallow anomaly detection L Ruff, JR Kauffmann, RA Vandermeulen, G Montavon, W Samek, M Kloft, ... Proceedings of the IEEE, 1-40, 2021	385	2021
Explaining recurrent neural network predictions in sentiment analysis L Arras, G Montavon, KR Müller, W Samek arXiv preprint arXiv:1706.07206, 2017	333	2017
Layer-wise relevance propagation for neural networks with local renormalization layers A Binder, G Montavon, S Lapuschkin, KR Müller, W Samek Artificial Neural Networks and Machine Learning–ICANN 2016: 25th …, 2016	308	2016
" What is relevant in a text document?": An interpretable machine learning approach L Arras, F Horn, G Montavon, KR Müller, W Samek PloS one 12 (8), e0181142, 2017	303	2017
iNNvestigate neural networks! M Alber, S Lapuschkin, P Seegerer, M Hägele, KT Schütt, G Montavon, ... J. Mach. Learn. Res. 20 (93), 1-8, 2019	299	2019
Analyzing classifiers: Fisher vectors and deep neural networks S Lapuschkin, A Binder, G Montavon, KR Muller, W Samek Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016	205	2016
Learning Invariant Representations of Molecules for Atomization Energy Prediction G Montavon, K Hansen, S Fazli, M Rupp, F Biegler, A Ziehe, ... Advances in Neural Information Processing Systems 25, 449-457, 2012	182*	2012
Layer-wise relevance propagation for deep neural network architectures A Binder, S Bach, G Montavon, KR Müller, W Samek Information science and applications (ICISA) 2016, 913-922, 2016	152	2016
The LRP toolbox for artificial neural networks S Lapuschkin, A Binder, G Montavon, KR Müller, W Samek The Journal of Machine Learning Research 17 (1), 3938-3942, 2016	148	2016

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