Gilles Louppe
16 papers · 2013–2024 · 3 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Bronze 🗺️ Taxonomy Completionist (30) 🌟 Keyword Trendsetter Combo (4)
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Keyword Pioneer
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Topic Evolution
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Trend Setter
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Unstoppable · Bronze
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Prolific Year · Productive
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Century Club · Bronze
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Keyword Collector
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Venues
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Research topics
Machine Learning
(15)
Artificial Intelligence
(11)
Optimization & Theory
(10)
Bayesian & Probabilistic · Artificial Intelligence
(7)
Deep Learning
(5)
Core AI
(4)
Core Methods
(4)
Models
(4)
Bayesian & Probabilistic · Machine Learning
(3)
Learning Types · Machine Learning
(3)
Application Areas
(2)
Learning Paradigms
(2)
Learning Types · Deep Learning
(2)
Architectures
(1)
Keywords
simulation-based inference
(5)
likelihood-free inference
(4)
bayesian inference
(3)
feature selection
(3)
tree-based method
(2)
markov chain monte carlo
(2)
mean decrease impurity
(2)
normalizing flow
(2)
feature relevance
(2)
uncertainty quantification
(2)
variable importance
(2)
random forest
(2)
empirical baye
(2)
bayesian inverse problem
(2)
variational inference
(2)
posterior inference
(2)
density estimation
(2)
posterior sampling
(1)
expectation maximization
(1)
ensemble learning
(1)
Papers
Learning Diffusion Priors from Observations by Expectation Maximization
NeurIPS 2024
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability
NeurIPS 2023
Score-based Data Assimilation
NeurIPS 2023
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation
NeurIPS 2022
From global to local MDI variable importances for random forests and when they are Shapley values
NeurIPS 2021
Graphical Normalizing Flows
AISTATS 2021
HNPE: Leveraging Global Parameters for Neural Posterior Estimation
NeurIPS 2021
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference
AISTATS 2021
Truncated Marginal Neural Ratio Estimation
NeurIPS 2021
Likelihood-free MCMC with Amortized Approximate Ratio Estimators
ICML 2020
Adversarial Variational Optimization of Non-Differentiable Simulators
AISTATS 2019
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
NeurIPS 2019
Unconstrained Monotonic Neural Networks
NeurIPS 2019
Random Subspace with Trees for Feature Selection Under Memory Constraints
AISTATS 2018
Learning to Pivot with Adversarial Networks
NeurIPS 2017
Understanding variable importances in forests of randomized trees
NeurIPS 2013