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Gr\'egoire Montavon

Identifiers

  • name variant Gr\'egoire Montavon 0.60 · backfill

Papers (26)

  1. Normalized Relevance Measure as a Unifying Framework to Explain Neural Network Latent Structures cs.LG · 2026 · author #3
  2. Conveyance: A Versatile Framework for Learning in Structured Class Spaces cs.LG · 2026 · author #2
  3. Relevant Walk Search for Explaining Graph Neural Networks cs.LG · 2026 · author #4
  4. Efficient Higher-order Subgraph Attribution via Message Passing cs.LG · 2026 · author #3
  5. Reliable Modeling of Distribution Shifts via Displacement-Reshaped Optimal Transport cs.LG · 2026 · author #4
  6. Mitigating Clever Hans Strategies in Image Classifiers through Generating Counterexamples cs.LG · 2025 · author #6
  7. Fast and Accurate Explanations of Distance-Based Classifiers by Uncovering Latent Explanatory Structures cs.LG · 2025 · author #5
  8. Unmasking Clever Hans Predictors and Assessing What Machines Really Learn cs.AI · 2019 · author #4
  9. iNNvestigate neural networks! cs.LG · 2018 · author #6
  10. Unsupervised Detection and Explanation of Latent-class Contextual Anomalies stat.ML · 2018 · author #2
  11. Understanding Patch-Based Learning by Explaining Predictions cs.LG · 2018 · author #2
  12. Discovering topics in text datasets by visualizing relevant words cs.CL · 2017 · author #3
  13. Exploring text datasets by visualizing relevant words cs.CL · 2017 · author #3
  14. Methods for Interpreting and Understanding Deep Neural Networks cs.LG · 2017 · author #1
  15. Explaining Recurrent Neural Network Predictions in Sentiment Analysis cs.CL · 2017 · author #2
  16. "What is Relevant in a Text Document?": An Interpretable Machine Learning Approach cs.CL · 2016 · author #3
  17. Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation stat.ML · 2016 · author #2
  18. Explaining Predictions of Non-Linear Classifiers in NLP cs.CL · 2016 · author #3
  19. Identifying individual facial expressions by deconstructing a neural network cs.CV · 2016 · author #2
  20. Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers cs.CV · 2016 · author #2
  21. Explaining NonLinear Classification Decisions with Deep Taylor Decomposition cs.LG · 2015 · author #1
  22. Analyzing Classifiers: Fisher Vectors and Deep Neural Networks cs.CV · 2015 · author #3
  23. Evaluating the visualization of what a Deep Neural Network has learned cs.CV · 2015 · author #3
  24. Wasserstein Training of Boltzmann Machines stat.ML · 2015 · author #1
  25. Machine Learning of Molecular Electronic Properties in Chemical Compound Space physics.chem-ph · 2013 · author #1
  26. 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