Grégoire Montavon
- Methods for Interpreting and Understanding Deep Neural Networks
2017/06/24 by Grégoire Montavon, Wojciech Samek, Klaus‐Robert Müller +1 · 1 voice · 68 citations
Computer Science · Mathematics · #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #Neural Networks and Applications #cs.LG #stat.ML
- Evaluating the visualization of what a Deep Neural Network has learned
2015/09/21 by Wojciech Samek, Alexander Binder, Samek, Wojciech +7 · 25 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · #Cell Image Analysis Techniques #Computer Vision and Pattern Recognition (cs.CV) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning and Data Classification
- Layer-wise Relevance Propagation for Neural Networks with Local\n Renormalization Layers
2016/04/04 by Alexander Binder, Binder, Alexander, Grégoire Montavon +7 · 23 citations
Computer Science · #Advanced Neural Network Applications #Medical Image Segmentation Techniques #Domain Adaptation and Few-Shot Learning
- XAI for Transformers: Better Explanations through Conservative Propagation
2022/02/15 by Ameen Ali, Ali, Ameen, Thomas Schnake +9 · 12 citations
Computer Science · #Explainable Artificial Intelligence (XAI) #Machine Learning and Data Classification #Anomaly Detection Techniques and Applications
- iNNvestigate neural networks!
2018/08/13 by Maximilian Alber, Alber, Maximilian, Sebastian Lapuschkin +17 · 6 citations
Computer Science · #Explainable Artificial Intelligence (XAI) #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning
- Wasserstein Training of Boltzmann Machines
2015/07/07 by Grégoire Montavon, Montavon, Grégoire, Klaus‐Robert Müller +3 · 3 citations
Computer Science · Engineering · Physics and Astronomy · #Generative Adversarial Networks and Image Synthesis #Lattice Boltzmann Simulation Studies #Model Reduction and Neural Networks
- MambaLRP: Explaining Selective State Space Sequence Models
2024/06/11 by Farnoush Rezaei Jafari, Grégoire Montavon, Jafari, Farnoush Rezaei +6 · 1 voice · 6 citations
Computer Science · Decision Sciences · Mathematics · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Simulation Techniques and Applications #cs.AI #cs.LG #stat.ML
- Analyzing Atomic Interactions in Molecules as Learned by Neural Networks
2025/01/10 by Malte Esders, Thomas Schnake, Jonas Lederer +4 · 1 voice · 5 citations
Materials Science · Computer Science · #Machine Learning in Materials Science #Computational Drug Discovery Methods #Topic Modeling
- Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation
2016/11/24 by Wojciech Samek, Grégoire Montavon, Samek, Wojciech +7 · 2 citations
Computer Science · #Explainable Artificial Intelligence (XAI) #Anomaly Detection Techniques and Applications #Machine Learning and Data Classification
- Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations
2022/11/22 by Alexander Binder, Leander Weber, Binder, Alexander +9 · 3 citations
Computer Science · Materials Science · #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #Machine Learning in Materials Science
- The Clever Hans Effect in Anomaly Detection
2020/06/18 by Jacob Kauffmann, Kauffmann, Jacob, Lukas Ruff +5 · 2 citations
Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces
2024/04/12 by Pattarawat Chormai, Jan Herrmann, Klaus‐Robert Müller +1 · 1 voice · 2 citations
Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Explainable Artificial Intelligence (XAI)
- Opportunities and limitations of explaining quantum machine learning
2024/12/19 by Elies Gil-Fuster, Jonas R. Naujoks, Gil-Fuster, Elies +9 · 2 citations
Materials Science · #Machine Learning in Materials Science