ML Anthology

Charpentier, Bertrand

17 publications

NeurIPS 2025 TreeGen: A Bayesian Generative Model for Hierarchies Marcel Kollovieh, Nils Fleischmann, Filippo Guerranti, Bertrand Charpentier, Stephan Günnemann
NeurIPS 2024 Expected Probabilistic Hierarchies Marcel Kollovieh, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
ICML 2024 Uncertainty for Active Learning on Graphs Dominik Fuchsgruber, Tom Wollschläger, Bertrand Charpentier, Antonio Oroz, Stephan Günnemann
NeurIPS 2023 Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
LoG 2023 Edge Directionality Improves Learning on Heterophilic Graphs Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein
ICLRW 2023 Training, Architecture, and Prior for Deterministic Uncertainty Methods Bertrand Charpentier, Chenxiang Zhang, Stephan Günnemann
ICML 2023 Uncertainty Estimation for Molecules: Desiderata and Methods Tom Wollschläger, Nicholas Gao, Bertrand Charpentier, Mohamed Amine Ketata, Stephan Günnemann
ICLR 2022 Differentiable DAG Sampling Bertrand Charpentier, Simon Kibler, Stephan Günnemann
ICLR 2022 End-to-End Learning of Probabilistic Hierarchies on Graphs Daniel Zügner, Bertrand Charpentier, Morgane Ayle, Sascha Geringer, Stephan Günnemann
ICLR 2022 Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions Bertrand Charpentier, Oliver Borchert, Daniel Zügner, Simon Geisler, Stephan Günnemann
ICML 2022 Winning the Lottery Ahead of Time: Efficient Early Network Pruning John Rachwan, Daniel Zügner, Bertrand Charpentier, Simon Geisler, Morgane Ayle, Stephan Günnemann
ICML 2021 Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-Based Models Reliable? Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zügner, Sandhya Giri, Stephan Günnemann
NeurIPS 2021 Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler, Bertrand Charpentier, Simon Geisler, Daniel Zügner, Stephan Günnemann
NeurIPS 2020 Posterior Network: Uncertainty Estimation Without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
MLOSS 2020 Scikit-Network: Graph Analysis in Python Thomas Bonald, Nathan de Lara, Quentin Lutz, Bertrand Charpentier
IJCAI 2019 Tree Sampling Divergence: An Information-Theoretic Metric for Hierarchical Graph Clustering Bertrand Charpentier, Thomas Bonald
NeurIPS 2019 Uncertainty on Asynchronous Time Event Prediction Marin Biloš, Bertrand Charpentier, Stephan Günnemann