Grégoire Montavon

108 papers A* 6A 1Journal 77Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Distilling Lightweight Domain Experts from Large ML Models by Identifying Relevant Subspaces. CoRR Pattarawat Chormai, Ali Hashemi, Klaus-Robert Müller, Grégoire Montavon
2026	J	`jnl`	Investigating the Robustness of Subtask Distillation under Spurious Correlation. CoRR Pattarawat Chormai, Klaus-Robert Müller, Grégoire Montavon
2026	J	`jnl`	Towards desiderata-driven design of visual counterfactual explainers. Pattern Recognit. Sidney Bender, Jan Herrmann, Klaus-Robert Müller, Grégoire Montavon
2026	J	`jnl`	Uncertainty Gating for Cost-Aware Explainable Artificial Intelligence. CoRR Georgii Mikriukov, Grégoire Montavon, Marina M.-C. Höhne
2025	J	`jnl`	Drainage: A Unifying Framework for Addressing Class Uncertainty. CoRR Yasser Taha, Grégoire Montavon, Nils Körber
2025	J	`jnl`	Explainable AI reveals Clever Hans effects in unsupervised learning models. Nat. Mac. Intell. Jacob R. Kauffmann, Jonas Dippel, Lukas Ruff, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon
2025	J	`jnl`	Explaining predictive uncertainty by exposing second-order effects. Pattern Recognit. Florian Bley, Sebastian Lapuschkin, Wojciech Samek, Grégoire Montavon
2025	J	`jnl`	Fast and Accurate Explanations of Distance-Based Classifiers by Uncovering Latent Explanatory Structures. CoRR Florian Bley, Jacob R. Kauffmann, Simon León Krug, Klaus-Robert Müller, Grégoire Montavon
2025	—	`conf`	MeDi: Metadata-Guided Diffusion Models for Mitigating Biases in Tumor Classification. MICCAI (14) David Jacob Drexlin, Jonas Dippel, Julius Hense, Niklas Prenißl, Grégoire Montavon, Frederick Klauschen, Klaus-Robert Müller
2025	J	`jnl`	MeDi: Metadata-Guided Diffusion Models for Mitigating Biases in Tumor Classification. CoRR David Jacob Drexlin, Jonas Dippel, Julius Hense, Niklas Prenißl, Grégoire Montavon, Frederick Klauschen, Klaus-Robert Müller
2025	J	`jnl`	Mitigating Clever Hans Strategies in Image Classifiers through Generating Counterexamples. CoRR Sidney Bender, Ole Delzer, Jan Herrmann, Heike Marxfeld, Klaus-Robert Müller, Grégoire Montavon
2025	J	`jnl`	Towards Desiderata-Driven Design of Visual Counterfactual Explainers. CoRR Sidney Bender, Jan Herrmann, Klaus-Robert Müller, Grégoire Montavon
2025	J	`jnl`	Towards symbolic XAI - explanation through human understandable logical relationships between features. Inf. Fusion Thomas Schnake, Farnoush Rezaei Jafari, Jonas Lederer, Ping Xiong, Shinichi Nakajima, Stefan Gugler, Grégoire Montavon, Klaus-Robert Müller
2025	—	`conf`	Uncovering the Structure of Explanation Quality with Spectral Analysis. xAI (3) Johannes Maeß, Grégoire Montavon, Shinichi Nakajima, Klaus-Robert Müller, Thomas Schnake
2025	J	`jnl`	Uncovering the Structure of Explanation Quality with Spectral Analysis. CoRR Johannes Maeß, Grégoire Montavon, Shinichi Nakajima, Klaus-Robert Müller, Thomas Schnake
2025	J	`jnl`	Wasserstein Distances Made Explainable: Insights into Dataset Shifts and Transport Phenomena. CoRR Philip Naumann, Jacob R. Kauffmann, Grégoire Montavon
2025	—	`conf`	XpertAI: Uncovering Regression Model Strategies for Sub-manifolds. xAI (3) Simon Letzgus, Klaus-Robert Müller, Grégoire Montavon
2024	J	`jnl`	Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces. IEEE Trans. Pattern Anal. Mach. Intell. Pattarawat Chormai, Jan Herrmann, Klaus-Robert Müller, Grégoire Montavon
2024	J	`jnl`	Explainable AI for time series via Virtual Inspection Layers. Pattern Recognit. Johanna Vielhaben, Sebastian Lapuschkin, Grégoire Montavon, Wojciech Samek
2024	J	`jnl`	Explaining Predictive Uncertainty by Exposing Second-Order Effects. CoRR Florian Bley, Sebastian Lapuschkin, Wojciech Samek, Grégoire Montavon
2024	J	`jnl`	From Clustering to Cluster Explanations via Neural Networks. IEEE Trans. Neural Networks Learn. Syst. Jacob R. Kauffmann, Malte Esders, Lukas Ruff, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
2024	—	`ed.`	Joint Proceedings of the xAI 2024 Late-breaking Work, Demos and Doctoral Consortium co-located with the 2nd World Conference on eXplainable Artificial Intelligence (xAI-2024), Valletta, Malta, July 17-19, 2024. xAI (Late-breaking Work, Demos, Doctoral Consortium) Luca Longo, Weiru Liu, Grégoire Montavon
2024	A*	`conf`	MambaLRP: Explaining Selective State Space Sequence Models. NeurIPS Farnoush Rezaei Jafari, Grégoire Montavon, Klaus-Robert Müller, Oliver Eberle
2024	J	`jnl`	MambaLRP: Explaining Selective State Space Sequence Models. CoRR Farnoush Rezaei Jafari, Grégoire Montavon, Klaus-Robert Müller, Oliver Eberle
2024	J	`jnl`	Opportunities and limitations of explaining quantum machine learning. CoRR Elies Gil-Fuster, Jonas R. Naujoks, Grégoire Montavon, Thomas Wiegand, Wojciech Samek, Jens Eisert
2024	J	`jnl`	Preemptively pruning Clever-Hans strategies in deep neural networks. Inf. Fusion Lorenz Linhardt, Klaus-Robert Müller, Grégoire Montavon
2024	J	`jnl`	The Clever Hans Effect in Unsupervised Learning. CoRR Jacob R. Kauffmann, Jonas Dippel, Lukas Ruff, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon
2024	J	`jnl`	Towards Symbolic XAI - Explanation Through Human Understandable Logical Relationships Between Features. CoRR Thomas Schnake, Farnoush Rezaei Jafari, Jonas Lederer, Ping Xiong, Shinichi Nakajima, Stefan Gugler, Grégoire Montavon, Klaus-Robert Müller
2024	J	`jnl`	XpertAI: uncovering model strategies for sub-manifolds. CoRR Simon Letzgus, Klaus-Robert Müller, Grégoire Montavon
2023	J	`jnl`	Explainable AI for Time Series via Virtual Inspection Layers. CoRR Johanna Vielhaben, Sebastian Lapuschkin, Grégoire Montavon, Wojciech Samek
2023	J	`jnl`	Insightful analysis of historical sources at scales beyond human capabilities using unsupervised Machine Learning and XAI. CoRR Oliver Eberle, Jochen Büttner, Hassan El-Hajj, Grégoire Montavon, Klaus-Robert Müller, Matteo Valleriani
2023	J	`jnl`	Learning domain invariant representations by joint Wasserstein distance minimization. Neural Networks Léo Andéol, Yusei Kawakami, Yuichiro Wada, Takafumi Kanamori, Klaus-Robert Müller, Grégoire Montavon
2023	J	`jnl`	Preemptively Pruning Clever-Hans Strategies in Deep Neural Networks. CoRR Lorenz Linhardt, Klaus-Robert Müller, Grégoire Montavon
2023	A*	`conf`	Relevant Walk Search for Explaining Graph Neural Networks. ICML Ping Xiong, Thomas Schnake, Michael Gastegger, Grégoire Montavon, Klaus-Robert Müller, Shinichi Nakajima
2023	A*	`conf`	Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. CVPR Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2023	—	`conf`	Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation. ICCV (Workshops) Sidney Bender, Christopher J. Anders, Pattarawat Chormai, Heike Marxfeld, Jan Herrmann, Grégoire Montavon
2023	J	`jnl`	Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation. CoRR Sidney Bender, Christopher J. Anders, Pattarawat Chormai, Heike Marxfeld, Jan Herrmann, Grégoire Montavon
2022	J	`jnl`	An Ever-Expanding Humanities Knowledge Graph: The Sphaera Corpus at the Intersection of Humanities, Data Management, and Machine Learning. Datenbank-Spektrum Hassan El-Hajj, Maryam Zamani, Jochen Büttner, Julius Martinetz, Oliver Eberle, Noga Shlomi, Anna Siebold, Grégoire Montavon, Klaus-Robert Müller, Holger Kantz, Matteo Valleriani
2022	J	`jnl`	Building and Interpreting Deep Similarity Models. IEEE Trans. Pattern Anal. Mach. Intell. Oliver Eberle, Jochen Büttner, Florian Kräutli, Klaus-Robert Müller, Matteo Valleriani, Grégoire Montavon
2022	J	`jnl`	Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces. CoRR Pattarawat Chormai, Jan Herrmann, Klaus-Robert Müller, Grégoire Montavon
2022	A*	`conf`	Efficient Computation of Higher-Order Subgraph Attribution via Message Passing. ICML Ping Xiong, Thomas Schnake, Grégoire Montavon, Klaus-Robert Müller, Shinichi Nakajima
2022	J	`jnl`	Higher-Order Explanations of Graph Neural Networks via Relevant Walks. IEEE Trans. Pattern Anal. Mach. Intell. Thomas Schnake, Oliver Eberle, Jonas Lederer, Shinichi Nakajima, Kristof T. Schütt, Klaus-Robert Müller, Grégoire Montavon
2022	J	`jnl`	Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. CoRR Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2022	J	`jnl`	Toward Explainable Artificial Intelligence for Regression Models: A methodological perspective. IEEE Signal Process. Mag. Simon Letzgus, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon
2022	A*	`conf`	XAI for Transformers: Better Explanations through Conservative Propagation. ICML Ameen Ali, Thomas Schnake, Oliver Eberle, Grégoire Montavon, Klaus-Robert Müller, Lior Wolf
2022	J	`jnl`	XAI for Transformers: Better Explanations through Conservative Propagation. CoRR Ameen Ali, Thomas Schnake, Oliver Eberle, Grégoire Montavon, Klaus-Robert Müller, Lior Wolf
2021	J	`jnl`	A Unifying Review of Deep and Shallow Anomaly Detection. Proc. IEEE Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller
2021	J	`jnl`	Deep learning for surrogate modelling of 2D mantle convection. CoRR Siddhant Agarwal, Nicola Tosi, Pan Kessel, Doris Breuer, Grégoire Montavon
2021	J	`jnl`	Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications. Proc. IEEE Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller
2021	J	`jnl`	Learning Domain Invariant Representations by Joint Wasserstein Distance Minimization. CoRR Léo Andéol, Yusei Kawakami, Yuichiro Wada, Takafumi Kanamori, Klaus-Robert Müller, Grégoire Montavon
2021	J	`jnl`	Toward Explainable AI for Regression Models. CoRR Simon Letzgus, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon
2020	J	`jnl`	A Unifying Review of Deep and Shallow Anomaly Detection. CoRR Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller
2020	J	`jnl`	Building and Interpreting Deep Similarity Models. CoRR Oliver Eberle, Jochen Büttner, Florian Kräutli, Klaus-Robert Müller, Matteo Valleriani, Grégoire Montavon
2020	—	`conf`	Explaining the Predictions of Unsupervised Learning Models. xxAI@ICML Grégoire Montavon, Jacob R. Kauffmann, Wojciech Samek, Klaus-Robert Müller
2020	J	`jnl`	GraphKKE: Graph Kernel Koopman Embedding for Human Microbiome Analysis. CoRR Kateryna Melnyk, Stefan Klus, Grégoire Montavon, Tim O. F. Conrad
2020	J	`jnl`	GraphKKE: graph Kernel Koopman embedding for human microbiome analysis. Appl. Netw. Sci. Kateryna Melnyk, Stefan Klus, Grégoire Montavon, Tim O. F. Conrad
2020	J	`jnl`	The Clever Hans Effect in Anomaly Detection. CoRR Jacob R. Kauffmann, Lukas Ruff, Grégoire Montavon, Klaus-Robert Müller
2020	J	`jnl`	Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond. CoRR Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller
2020	J	`jnl`	Towards explaining anomalies: A deep Taylor decomposition of one-class models. Pattern Recognit. Jacob R. Kauffmann, Klaus-Robert Müller, Grégoire Montavon
2020	J	`jnl`	XAI for Graphs: Explaining Graph Neural Network Predictions by Identifying Relevant Walks. CoRR Thomas Schnake, Oliver Eberle, Jonas Lederer, Shinichi Nakajima, Kristof T. Schütt, Klaus-Robert Müller, Grégoire Montavon
2019	—	`book`	Explainable AI: Interpreting, Explaining and Visualizing Deep Learning Explainable AI Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, Lars Kai Hansen, Klaus-Robert Müller
2019	J	`jnl`	Explaining and Interpreting LSTMs. CoRR Leila Arras, Jose A. Arjona-Medina, Michael Widrich, Grégoire Montavon, Michael Gillhofer, Klaus-Robert Müller, Sepp Hochreiter, Wojciech Samek
2019	—	`ch.`	Explaining and Interpreting LSTMs. Explainable AI Leila Arras, Jose A. Arjona-Medina, Michael Widrich, Grégoire Montavon, Michael Gillhofer, Klaus-Robert Müller, Sepp Hochreiter, Wojciech Samek
2019	J	`jnl`	From Clustering to Cluster Explanations via Neural Networks. CoRR Jacob R. Kauffmann, Malte Esders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
2019	—	`ch.`	Gradient-Based Vs. Propagation-Based Explanations: An Axiomatic Comparison. Explainable AI Grégoire Montavon
2019	—	`ch.`	Layer-Wise Relevance Propagation: An Overview. Explainable AI Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Wojciech Samek, Klaus-Robert Müller
2019	—	`ch.`	Understanding Patch-Based Learning of Video Data by Explaining Predictions. Explainable AI Christopher J. Anders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
2019	J	`jnl`	Unmasking Clever Hans Predictors and Assessing What Machines Really Learn. CoRR Sebastian Lapuschkin, Stephan Wäldchen, Alexander Binder, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
2019	J	`jnl`	iNNvestigate Neural Networks! J. Mach. Learn. Res. Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans
2018	J	`jnl`	Methods for interpreting and understanding deep neural networks. Digit. Signal Process. Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
2018	J	`jnl`	Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models. CoRR Jacob R. Kauffmann, Klaus-Robert Müller, Grégoire Montavon
2018	J	`jnl`	Understanding Patch-Based Learning by Explaining Predictions. CoRR Christopher J. Anders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
2018	J	`jnl`	Unsupervised Detection and Explanation of Latent-class Contextual Anomalies. CoRR Jacob R. Kauffmann, Grégoire Montavon, Luiz Alberto Lima, Shinichi Nakajima, Klaus-Robert Müller, Nico Görnitz
2018	J	`jnl`	iNNvestigate neural networks! CoRR Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans
2017	J	`jnl`	Discovering topics in text datasets by visualizing relevant words. CoRR Franziska Horn, Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2017	J	`jnl`	Evaluating the Visualization of What a Deep Neural Network Has Learned. IEEE Trans. Neural Networks Learn. Syst. Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller
2017	—	`conf`	Explaining Recurrent Neural Network Predictions in Sentiment Analysis. WASSA@EMNLP Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2017	J	`jnl`	Explaining Recurrent Neural Network Predictions in Sentiment Analysis. CoRR Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2017	J	`jnl`	Explaining nonlinear classification decisions with deep Taylor decomposition. Pattern Recognit. Grégoire Montavon, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek, Klaus-Robert Müller
2017	J	`jnl`	Exploring text datasets by visualizing relevant words. CoRR Franziska Horn, Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2017	J	`jnl`	Methods for Interpreting and Understanding Deep Neural Networks. CoRR Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
2016	J	`jnl`	"What is Relevant in a Text Document?": An Interpretable Machine Learning Approach. CoRR Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2016	A*	`conf`	Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CVPR Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2016	—	`conf`	Explaining Predictions of Non-Linear Classifiers in NLP. Rep4NLP@ACL Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2016	J	`jnl`	Explaining Predictions of Non-Linear Classifiers in NLP. CoRR Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2016	—	`conf`	Identifying Individual Facial Expressions by Deconstructing a Neural Network. GCPR Farhad Arbabzadah, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2016	J	`jnl`	Identifying individual facial expressions by deconstructing a neural network. CoRR Farhad Arbabzadah, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2016	J	`jnl`	Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation. CoRR Wojciech Samek, Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Klaus-Robert Müller
2016	—	`conf`	Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers. ICANN (2) Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller, Wojciech Samek
2016	J	`jnl`	Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers. CoRR Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller, Wojciech Samek
2016	J	`jnl`	The LRP Toolbox for Artificial Neural Networks. J. Mach. Learn. Res. Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2016	—	`conf`	Wasserstein Training of Restricted Boltzmann Machines. NIPS Grégoire Montavon, Klaus-Robert Müller, Marco Cuturi
2015	J	`jnl`	Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CoRR Sebastian Bach, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
2015	J	`jnl`	Evaluating the visualization of what a Deep Neural Network has learned. CoRR Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller
2015	J	`jnl`	Explaining NonLinear Classification Decisions with Deep Taylor Decomposition. CoRR Grégoire Montavon, Sebastian Bach, Alexander Binder, Wojciech Samek, Klaus-Robert Müller
2015	J	`jnl`	Wasserstein Training of Boltzmann Machines. CoRR Grégoire Montavon, Klaus-Robert Müller, Marco Cuturi
2013	J	`jnl`	Analyzing Local Structure in Kernel-Based Learning: Explanation, Complexity, and Reliability Assessment. IEEE Signal Process. Mag. Grégoire Montavon, Mikio L. Braun, Tammo Krueger, Klaus-Robert Müller
2013	—	`—`	On layer-wise representations in deep neural networks. Grégoire Montavon
2012	—	`ch.`	Better Representations: Invariant, Disentangled and Reusable. Neural Networks: Tricks of the Trade (2nd ed.) Grégoire Montavon, Klaus-Robert Müller
2012	—	`ch.`	Big Learning and Deep Neural Networks. Neural Networks: Tricks of the Trade (2nd ed.) Grégoire Montavon, Klaus-Robert Müller
2012	—	`ch.`	Deep Boltzmann Machines and the Centering Trick. Neural Networks: Tricks of the Trade (2nd ed.) Grégoire Montavon, Klaus-Robert Müller
2012	A	`conf`	Deep Boltzmann Machines as Feed-Forward Hierarchies. AISTATS Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller
2012	—	`ch.`	Identifying Dynamical Systems for Forecasting and Control. Neural Networks: Tricks of the Trade (2nd ed.) Grégoire Montavon, Klaus-Robert Müller
2012	J	`jnl`	Learning Feature Hierarchies with Centered Deep Boltzmann Machines CoRR Grégoire Montavon, Klaus-Robert Müller
2012	—	`conf`	Learning Invariant Representations of Molecules for Atomization Energy Prediction. NIPS Grégoire Montavon, Katja Hansen, Siamac Fazli, Matthias Rupp, Franziska Biegler, Andreas Ziehe, Alexandre Tkatchenko, O. Anatole von Lilienfeld, Klaus-Robert Müller
2012	—	`book`	Neural Networks: Tricks of the Trade - Second Edition Neural Networks: Tricks of the Trade (2nd ed.) Grégoire Montavon, Genevieve B. Orr, Klaus-Robert Müller
2011	J	`jnl`	Kernel Analysis of Deep Networks. J. Mach. Learn. Res. Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller
2010	—	`conf`	Layer-wise analysis of deep networks with Gaussian kernels. NIPS Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller