Skip to content
conftrace_

Pierre-Alexandre Mattei

13 papers · 2016–2026 · 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

Jump to papers ↓
+3 more ↓ 🗺️ Taxonomy Completionist (19) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Half 🐣 Hot Topic Early Bird 🧬 Topic Evolution
💎 Century Club · Bronze 🗃️ Keyword Collector (59) ❓ The Questioner (3)

Venues

ICML (4) ICLR (3) AISTATS (2) NeurIPS (2) JMLR (1) UAI (1)

Top co-authors

Jes Frellsen (7) Charles Bouveyron (3) Hugo Schmutz (3) Damien Garreau (3) Niels Bruun Ipsen (2) Olivier HUMBERT (2) Frederic Precioso (2) Pierre Latouche (1) Warith HARCHAOUI (1) Soren Hauberg (1)

Research topics

Machine Learning (10) Deep Learning (7) Core Methods (6) Learning Types · Machine Learning (6) Artificial Intelligence (5) Optimization & Theory (5) Models (4) Learning Types · Deep Learning (3) Bayesian & Probabilistic (2) Core AI (2) Learning Paradigms (1)

Keywords

missing data (4) deep latent variable model (4) variational inference (4) neural network (2) deep ensemble (2) generative model (2) semi-supervised learning (2) model calibration (1) statistical learning theory (1) statistical inference (1) discriminative clustering (1) kullback-leibler divergence (1) probabilistic pca (1) sparse pca (1) mutual information (1) generalization error bound (1) statistical testing (1) false positive rate (1) unsupervised feature selection (1) feature importance (1)

Papers

Beyond Mixtures and Products for Ensemble Aggregation: A Likelihood Perspective on Generalized Means UAI 2026 Are Ensembles Getting Better All the Time? JMLR 2025 Are labels informative in semi-supervised learning? Estimating and leveraging the missing-data mechanism. ICML 2023 Don’t fear the unlabelled: safe semi-supervised learning via debiasing ICLR 2023 Explainability as statistical inference ICML 2023 Generalised Mutual Information for Discriminative Clustering NeurIPS 2022 How to deal with missing data in supervised deep learning? ICLR 2022 Model-agnostic out-of-distribution detection using combined statistical tests AISTATS 2022 not-MIWAE: Deep Generative Modelling with Missing not at Random Data ICLR 2021 MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets ICML 2019 Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation ICML 2019 Leveraging the Exact Likelihood of Deep Latent Variable Models NeurIPS 2018 Globally Sparse Probabilistic PCA AISTATS 2016