Gr\'egoire Montavon
Identifiers
- name variant Gr\'egoire Montavon 0.60 · backfill
Papers (26)
- Normalized Relevance Measure as a Unifying Framework to Explain Neural Network Latent Structures cs.LG · 2026 · author #3
- Conveyance: A Versatile Framework for Learning in Structured Class Spaces cs.LG · 2026 · author #2
- Relevant Walk Search for Explaining Graph Neural Networks cs.LG · 2026 · author #4
- Efficient Higher-order Subgraph Attribution via Message Passing cs.LG · 2026 · author #3
- Reliable Modeling of Distribution Shifts via Displacement-Reshaped Optimal Transport cs.LG · 2026 · author #4
- Mitigating Clever Hans Strategies in Image Classifiers through Generating Counterexamples cs.LG · 2025 · author #6
- Fast and Accurate Explanations of Distance-Based Classifiers by Uncovering Latent Explanatory Structures cs.LG · 2025 · author #5
- Unmasking Clever Hans Predictors and Assessing What Machines Really Learn cs.AI · 2019 · author #4
- iNNvestigate neural networks! cs.LG · 2018 · author #6
- Unsupervised Detection and Explanation of Latent-class Contextual Anomalies stat.ML · 2018 · author #2
- Understanding Patch-Based Learning by Explaining Predictions cs.LG · 2018 · author #2
- Discovering topics in text datasets by visualizing relevant words cs.CL · 2017 · author #3
- Exploring text datasets by visualizing relevant words cs.CL · 2017 · author #3
- Methods for Interpreting and Understanding Deep Neural Networks cs.LG · 2017 · author #1
- Explaining Recurrent Neural Network Predictions in Sentiment Analysis cs.CL · 2017 · author #2
- "What is Relevant in a Text Document?": An Interpretable Machine Learning Approach cs.CL · 2016 · author #3
- Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation stat.ML · 2016 · author #2
- Explaining Predictions of Non-Linear Classifiers in NLP cs.CL · 2016 · author #3
- Identifying individual facial expressions by deconstructing a neural network cs.CV · 2016 · author #2
- Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers cs.CV · 2016 · author #2
- Explaining NonLinear Classification Decisions with Deep Taylor Decomposition cs.LG · 2015 · author #1
- Analyzing Classifiers: Fisher Vectors and Deep Neural Networks cs.CV · 2015 · author #3
- Evaluating the visualization of what a Deep Neural Network has learned cs.CV · 2015 · author #3
- Wasserstein Training of Boltzmann Machines stat.ML · 2015 · author #1
- Machine Learning of Molecular Electronic Properties in Chemical Compound Space physics.chem-ph · 2013 · author #1
- Learning Feature Hierarchies with Centered Deep Boltzmann Machines stat.ML · 2012 · author #1
Mentions
- 1509.06321 #3 · backfill · confidence 0.70 Gr\'egoire Montavon
- 1507.01972 #1 · backfill · confidence 0.70 Gr\'egoire Montavon
- 2606.00557 #3 · arxiv_oai · confidence 0.70 Gr\'egoire Montavon
- 2605.28420 #2 · arxiv_oai · confidence 0.70 Gr\'egoire Montavon
- 1305.7074 #1 · backfill · confidence 0.70 Gr\'egoire Montavon
- 2605.23673 #4 · arxiv_oai · confidence 0.70 Gr\'egoire Montavon
- 1203.3783 #1 · backfill · confidence 0.70 Gr\'egoire Montavon
- 2605.22385 #3 · arxiv_oai · confidence 0.70 Gr\'egoire Montavon
Frequent Coauthors
- Klaus-Robert M\"uller 25 shared papers
- Wojciech Samek 15 shared papers
- Alexander Binder 6 shared papers
- Leila Arras 5 shared papers
- Franziska Horn 4 shared papers
- Sebastian Bach 4 shared papers
- Shinichi Nakajima 4 shared papers
- Jacob Kauffmann 3 shared papers
- Ping Xiong 3 shared papers
- Sebastian Lapuschkin 3 shared papers
- Thomas Schnake 3 shared papers
- Alexandre Tkatchenko 1 shared papers
- Alvaro Vazquez-Mayagoitia 1 shared papers
- Christopher Anders 1 shared papers
- Farhad Arbabzadah 1 shared papers
- Florian Bley 1 shared papers
- Heike Antje Marxfeld 1 shared papers
- Jan Herrmann 1 shared papers
- Katja Hansen 1 shared papers
- Kristof T. Sch\"utt 1 shared papers