Alix LHERITIER

4 papers · 2019–2025 · 3 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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🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (15)

Venues

AISTATS (2) ICLR (1) NeurIPS (1)

Top co-authors

Frederic Cazals (1) Maurizio Filippone (1) Nicolas Bondoux (1)

Research topics

Machine Learning (4) Artificial Intelligence (3) Bayesian & Probabilistic · Artificial Intelligence (3) Bayesian & Probabilistic · Machine Learning (2) Core Methods (2) Learning Types (2) Optimization & Theory (2) Deep Learning (1) Reinforcement Learning (1) Core AI (1) Methods (1) Models (1)

Keywords

wasserstein distance (1) nonparametric bayesian (1) distributional reinforcement learning (1) maximum likelihood (1) conditional entropy (1) quantile regression (1) k-d tree (1) markov chain (1) online prediction (1) log loss (1) choice modeling (1) gaussian copula (1) amortized inference (1) value-based learning (1) bayesian neural network (1) conditional density estimation (1) mixture density network (1) prior predictive distribution (1) beta distribution (1) value distribution (1)

Papers

Unconditionally Calibrated Priors for Beta Mixture Density Networks AISTATS 2025 A Cramér Distance perspective on Quantile Regression based Distributional Reinforcement Learning AISTATS 2022 PCMC-Net: Feature-based Pairwise Choice Markov Chains ICLR 2020 Low-Complexity Nonparametric Bayesian Online Prediction with Universal Guarantees NeurIPS 2019