Grégoire Montavon
15 papers · 2010–2026 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🗺️ Taxonomy Completionist (27) 🏃 Academic Marathon · Full 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Topic Evolution
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Keyword Pioneer
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Keyword Trendsetter Combo
(8)
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Keyword Champion
(5)
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Dynamic Duo
(13)
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Trend Setter
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Unstoppable · Bronze
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Century Club · Bronze
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Top co-authors
Research topics
Deep Learning
(13)
Machine Learning
(10)
Architectures
(10)
Artificial Intelligence
(7)
Core AI
(7)
Core Methods
(6)
Learning Types · Deep Learning
(4)
Learning Types · Machine Learning
(3)
Optimization & Theory
(3)
Application Areas
(2)
Models
(2)
Computer Science
(1)
Healthcare & Medicine
(1)
Interdisciplinary
(1)
Applications
(1)
Keywords
layer-wise relevance propagation
(5)
image classification
(3)
representation learning
(3)
neural network
(3)
graph neural network
(3)
feature attribution
(2)
deep network
(2)
generative model
(2)
invariant representation
(2)
max-product algorithm
(1)
gaussian kernel
(1)
kullback-leibler divergence
(1)
graph representation
(1)
layer-wise analysis
(1)
message passing
(1)
hierarchical representation
(1)
explainable ai
(1)
quantum mechanical energies
(1)
graph-like molecular data
(1)
molecular machine learning
(1)
Papers
Drainage: A Unifying Framework for Addressing Class Uncertainty
CVPR 2026
MeDi: Metadata-Guided Diffusion Models for Mitigating Biases in Tumor Classification
MICCAI 2025
MambaLRP: Explaining Selective State Space Sequence Models
NeurIPS 2024
Relevant Walk Search for Explaining Graph Neural Networks
ICML 2023
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations
CVPR 2023
Efficient Computation of Higher-Order Subgraph Attribution via Message Passing
ICML 2022
XAI for Transformers: Better Explanations through Conservative Propagation
ICML 2022
iNNvestigate Neural Networks!
JMLR 2019
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks
CVPR 2016
The LRP Toolbox for Artificial Neural Networks
JMLR 2016
Wasserstein Training of Restricted Boltzmann Machines
NeurIPS 2016
Deep Boltzmann Machines as Feed-Forward Hierarchies
AISTATS 2012
Learning Invariant Representations of Molecules for Atomization Energy Prediction
NeurIPS 2012
Kernel Analysis of Deep Networks
JMLR 2011
Layer-wise analysis of deep networks with Gaussian kernels
NeurIPS 2010