Bertrand Charpentier
14 papers · 2019–2024 · 5 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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🌉 Interdisciplinary Bridge · Gold 🗺️ Taxonomy Completionist (30) 🌍 Conference Polyglot · Silver 🐣 Hot Topic Early Bird 🏃 Academic Marathon · Sprint
🤝
Dynamic Duo
(12)
❓
The Questioner
🔥
Unstoppable · Bronze
💎
Century Club · Bronze
🗃️
Keyword Collector
(65)
Venues
Top co-authors
Research topics
Machine Learning
(13)
Deep Learning
(8)
Optimization & Theory
(8)
Core Methods
(7)
Artificial Intelligence
(6)
Architectures
(5)
Bayesian & Probabilistic · Artificial Intelligence
(5)
Learning Types
(4)
Bayesian & Probabilistic · Machine Learning
(3)
Data Science & Analytics
(2)
Mathematics & Optimization
(2)
Core AI
(2)
Mathematics
(2)
Models
(2)
Computer Science
(1)
Keywords
graph neural network
(5)
out-of-distribution detection
(4)
uncertainty quantification
(3)
uncertainty estimation
(3)
hierarchical clustering
(3)
graph clustering
(3)
probabilistic model
(2)
normalizing flow
(2)
bayesian inference
(2)
tree-sampling divergence
(2)
gaussian process
(2)
dirichlet distribution
(2)
node classification
(2)
causal discovery
(1)
semi-supervised learning
(1)
label propagation
(1)
link prediction
(1)
unsupervised learning
(1)
adversarial training
(1)
bayesian learning
(1)
Papers
Expected Probabilistic Hierarchies
NeurIPS 2024
Uncertainty for Active Learning on Graphs
ICML 2024
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions
NeurIPS 2023
Uncertainty Estimation for Molecules: Desiderata and Methods
ICML 2023
Differentiable DAG Sampling
ICLR 2022
End-to-End Learning of Probabilistic Hierarchies on Graphs
ICLR 2022
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions
ICLR 2022
Winning the Lottery Ahead of Time: Efficient Early Network Pruning
ICML 2022
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
ICML 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification
NeurIPS 2021
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts
NeurIPS 2020
Scikit-network: Graph Analysis in Python
JMLR 2020
Tree Sampling Divergence: An Information-Theoretic Metric for Hierarchical Graph Clustering
IJCAI 2019
Uncertainty on Asynchronous Time Event Prediction
NeurIPS 2019