Grégoire Montavon

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 64

Top Venues

CoRR

Pattern Recognit.

ICML

IEEE Trans. Neural Networks Learn. Syst.

Berlin Institute of Technology (PHD)

Education History

Berlin Institute of Technology

PHD

Publications

Jacob R. Kauffmann, Malte Esders, Lukas Ruff, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
From Clustering to Cluster Explanations via Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35 (2) (2024)
Lorenz Linhardt, Klaus-Robert Müller, Grégoire Montavon
Preemptively pruning Clever-Hans strategies in deep neural networks. Inf. Fusion 103 (2024)
Farnoush Rezaei Jafari, Grégoire Montavon, Klaus-Robert Müller, Oliver Eberle
MambaLRP: Explaining Selective State Space Sequence Models. CoRR (2024)
Florian Bley, Sebastian Lapuschkin, Wojciech Samek, Grégoire Montavon
Explaining Predictive Uncertainty by Exposing Second-Order Effects. CoRR (2024)
Simon Letzgus, Klaus-Robert Müller, Grégoire Montavon
XpertAI: uncovering model strategies for sub-manifolds. CoRR (2024)
Johanna Vielhaben, Sebastian Lapuschkin, Grégoire Montavon, Wojciech Samek
Explainable AI for time series via Virtual Inspection Layers. Pattern Recognit. 150 (2024)
Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. CVPR (2023)
Léo Andéol, Yusei Kawakami, Yuichiro Wada, Takafumi Kanamori, Klaus-Robert Müller, Grégoire Montavon
Learning domain invariant representations by joint Wasserstein distance minimization. Neural Networks 167 (2023)
Ping Xiong, Thomas Schnake, Michael Gastegger, Grégoire Montavon, Klaus-Robert Müller, Shinichi Nakajima
Relevant Walk Search for Explaining Graph Neural Networks. ICML (2023)
Lorenz Linhardt, Klaus-Robert Müller, Grégoire Montavon
Preemptively Pruning Clever-Hans Strategies in Deep Neural Networks. CoRR (2023)
Johanna Vielhaben, Sebastian Lapuschkin, Grégoire Montavon, Wojciech Samek
Explainable AI for Time Series via Virtual Inspection Layers. CoRR (2023)
Sidney Bender, Christopher J. Anders, Pattarawat Chormai, Heike Marxfeld, Jan Herrmann, Grégoire Montavon
Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation. ICCV (Workshops) (2023)
Sidney Bender, Christopher J. Anders, Pattarawat Chormai, Heike Marxfeld, Jan Herrmann, Grégoire Montavon
Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation. CoRR (2023)
Oliver Eberle, Jochen Büttner, Hassan El-Hajj, Grégoire Montavon, Klaus-Robert Müller, Matteo Valleriani
Insightful analysis of historical sources at scales beyond human capabilities using unsupervised Machine Learning and XAI. CoRR (2023)
Oliver Eberle, Jochen Büttner, Florian Kräutli, Klaus-Robert Müller, Matteo Valleriani, Grégoire Montavon
Building and Interpreting Deep Similarity Models. IEEE Trans. Pattern Anal. Mach. Intell. 44 (3) (2022)
Pattarawat Chormai, Jan Herrmann, Klaus-Robert Müller, Grégoire Montavon
Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces. CoRR (2022)
Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. CoRR (2022)
Ping Xiong, Thomas Schnake, Grégoire Montavon, Klaus-Robert Müller, Shinichi Nakajima
Efficient Computation of Higher-Order Subgraph Attribution via Message Passing. ICML (2022)
Simon Letzgus, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon
Toward Explainable Artificial Intelligence for Regression Models: A methodological perspective. IEEE Signal Process. Mag. 39 (4) (2022)
Ameen Ali, Thomas Schnake, Oliver Eberle, Grégoire Montavon, Klaus-Robert Müller, Lior Wolf
XAI for Transformers: Better Explanations through Conservative Propagation. ICML (2022)
Thomas Schnake, Oliver Eberle, Jonas Lederer, Shinichi Nakajima, Kristof T. Schütt, Klaus-Robert Müller, Grégoire Montavon
Higher-Order Explanations of Graph Neural Networks via Relevant Walks. IEEE Trans. Pattern Anal. Mach. Intell. 44 (11) (2022)
Ameen Ali, Thomas Schnake, Oliver Eberle, Grégoire Montavon, Klaus-Robert Müller, Lior Wolf
XAI for Transformers: Better Explanations through Conservative Propagation. CoRR (2022)
Hassan El-Hajj, Maryam Zamani, Jochen Büttner, Julius Martinetz, Oliver Eberle, Noga Shlomi, Anna Siebold, Grégoire Montavon, Klaus-Robert Müller, Holger Kantz, Matteo Valleriani
An Ever-Expanding Humanities Knowledge Graph: The Sphaera Corpus at the Intersection of Humanities, Data Management, and Machine Learning. Datenbank-Spektrum 22 (2) (2022)
Siddhant Agarwal, Nicola Tosi, Pan Kessel, Doris Breuer, Grégoire Montavon
Deep learning for surrogate modelling of 2D mantle convection. CoRR (2021)
Simon Letzgus, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon
Toward Explainable AI for Regression Models. CoRR (2021)
Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications. Proc. IEEE 109 (3) (2021)
Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller
A Unifying Review of Deep and Shallow Anomaly Detection. Proc. IEEE 109 (5) (2021)
Léo Andéol, Yusei Kawakami, Yuichiro Wada, Takafumi Kanamori, Klaus-Robert Müller, Grégoire Montavon
Learning Domain Invariant Representations by Joint Wasserstein Distance Minimization. CoRR (2021)
Jacob R. Kauffmann, Klaus-Robert Müller, Grégoire Montavon
Towards explaining anomalies: A deep Taylor decomposition of one-class models. Pattern Recognit. 101 (2020)
Kateryna Melnyk, Stefan Klus, Grégoire Montavon, Tim O. F. Conrad
GraphKKE: Graph Kernel Koopman Embedding for Human Microbiome Analysis. CoRR (2020)
Jacob R. Kauffmann, Lukas Ruff, Grégoire Montavon, Klaus-Robert Müller
The Clever Hans Effect in Anomaly Detection. CoRR (2020)
Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller
A Unifying Review of Deep and Shallow Anomaly Detection. CoRR (2020)
Grégoire Montavon, Jacob R. Kauffmann, Wojciech Samek, Klaus-Robert Müller
Explaining the Predictions of Unsupervised Learning Models. xxAI@ICML (2020)
Thomas Schnake, Oliver Eberle, Jonas Lederer, Shinichi Nakajima, Kristof T. Schütt, Klaus-Robert Müller, Grégoire Montavon
XAI for Graphs: Explaining Graph Neural Network Predictions by Identifying Relevant Walks. CoRR (2020)
Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller
Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond. CoRR (2020)
Oliver Eberle, Jochen Büttner, Florian Kräutli, Klaus-Robert Müller, Matteo Valleriani, Grégoire Montavon
Building and Interpreting Deep Similarity Models. CoRR (2020)
Kateryna Melnyk, Stefan Klus, Grégoire Montavon, Tim O. F. Conrad
GraphKKE: graph Kernel Koopman embedding for human microbiome analysis. Appl. Netw. Sci. 5 (1) (2020)
Jacob R. Kauffmann, Malte Esders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
From Clustering to Cluster Explanations via Neural Networks. CoRR (2019)
Sebastian Lapuschkin, Stephan Wäldchen, Alexander Binder, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn. CoRR (2019)
Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans
iNNvestigate Neural Networks! J. Mach. Learn. Res. 20 (2019)
Leila Arras, Jose A. Arjona-Medina, Michael Widrich, Grégoire Montavon, Michael Gillhofer, Klaus-Robert Müller, Sepp Hochreiter, Wojciech Samek
Explaining and Interpreting LSTMs. CoRR (2019)
Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
Methods for interpreting and understanding deep neural networks. Digit. Signal Process. 73 (2018)
Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans
iNNvestigate neural networks! CoRR (2018)
Jacob R. Kauffmann, Klaus-Robert Müller, Grégoire Montavon
Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models. CoRR (2018)
Jacob R. Kauffmann, Grégoire Montavon, Luiz Alberto Lima, Shinichi Nakajima, Klaus-Robert Müller, Nico Görnitz
Unsupervised Detection and Explanation of Latent-class Contextual Anomalies. CoRR (2018)
Christopher J. Anders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
Understanding Patch-Based Learning by Explaining Predictions. CoRR (2018)
Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Explaining Recurrent Neural Network Predictions in Sentiment Analysis. CoRR (2017)
Franziska Horn, Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Discovering topics in text datasets by visualizing relevant words. CoRR (2017)
Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Explaining Recurrent Neural Network Predictions in Sentiment Analysis. WASSA@EMNLP (2017)
Franziska Horn, Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Exploring text datasets by visualizing relevant words. CoRR (2017)
Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
Methods for Interpreting and Understanding Deep Neural Networks. CoRR (2017)
Grégoire Montavon, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek, Klaus-Robert Müller
Explaining nonlinear classification decisions with deep Taylor decomposition. Pattern Recognit. 65 (2017)
Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller
Evaluating the Visualization of What a Deep Neural Network Has Learned. IEEE Trans. Neural Networks Learn. Syst. 28 (11) (2017)
Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CVPR (2016)
Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller, Wojciech Samek
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers. CoRR (2016)
Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
"What is Relevant in a Text Document?": An Interpretable Machine Learning Approach. CoRR (2016)
Farhad Arbabzadah, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Identifying Individual Facial Expressions by Deconstructing a Neural Network. GCPR (2016)
Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Explaining Predictions of Non-Linear Classifiers in NLP. Rep4NLP@ACL (2016)
Farhad Arbabzadah, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Identifying individual facial expressions by deconstructing a neural network. CoRR (2016)
Wojciech Samek, Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Klaus-Robert Müller
Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation. CoRR (2016)
Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Explaining Predictions of Non-Linear Classifiers in NLP. CoRR (2016)
Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller, Wojciech Samek
Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers. ICANN (2) (2016)
Grégoire Montavon, Klaus-Robert Müller, Marco Cuturi
Wasserstein Training of Restricted Boltzmann Machines. NIPS (2016)
Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
The LRP Toolbox for Artificial Neural Networks. J. Mach. Learn. Res. 17 (2016)
Grégoire Montavon, Klaus-Robert Müller, Marco Cuturi
Wasserstein Training of Boltzmann Machines. CoRR (2015)
Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller
Evaluating the visualization of what a Deep Neural Network has learned. CoRR (2015)
Grégoire Montavon, Sebastian Bach, Alexander Binder, Wojciech Samek, Klaus-Robert Müller
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition. CoRR (2015)
Sebastian Bach, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CoRR (2015)
Grégoire Montavon, Mikio L. Braun, Tammo Krueger, Klaus-Robert Müller
Analyzing Local Structure in Kernel-Based Learning: Explanation, Complexity, and Reliability Assessment. IEEE Signal Process. Mag. 30 (4) (2013)
Grégoire Montavon, Klaus-Robert Müller
Learning Feature Hierarchies with Centered Deep Boltzmann Machines CoRR (2012)
Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller
Deep Boltzmann Machines as Feed-Forward Hierarchies. AISTATS (2012)
Grégoire Montavon, Katja Hansen, Siamac Fazli, Matthias Rupp, Franziska Biegler, Andreas Ziehe, Alexandre Tkatchenko, O. Anatole von Lilienfeld, Klaus-Robert Müller
Learning Invariant Representations of Molecules for Atomization Energy Prediction. NIPS (2012)
Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller
Kernel Analysis of Deep Networks. J. Mach. Learn. Res. 12 (2011)
Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller
Layer-wise analysis of deep networks with Gaussian kernels. NIPS (2010)

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Publication Activity (10 Years)

Top Topics

Top Venues

Grégoire Montavon