Cover Image

Bayesian Active Learning of (small) Quantile Sets through Expected Estimator Modification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Abdelmalek-Lomenech, Romain Ait, Bect, Julien, Vazquez, Emmanuel
Format:	Preprint
Published:	2025
Subjects:	Applications Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Bayesian sequential design of computer experiments for quantile set inversion
by: Abdelmalek-Lomenech, Romain Ait, et al.
Published: (2022)

Sequential design of multi-fidelity computer experiments: maximizing the rate of stepwise uncertainty reduction
by: Stroh, Rémi, et al.
Published: (2020)

Bayesian Estimation of Extreme Quantiles and the Exceedance Distribution for Paretian Tails
by: Johnston, Douglas E.
Published: (2025)

Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
by: Petit, Sébastien, et al.
Published: (2022)

Expected Diverse Utility (EDU): Diverse Bayesian Optimization of Expensive Computer Simulators
by: Miller, John Joshua, et al.
Published: (2024)

Bayes-xG: Player and Position Correction on Expected Goals (xG) using Bayesian Hierarchical Approach
by: Scholtes, Alexander, et al.
Published: (2023)

Integrating Marketing Channels into Quantile Transformation and Bayesian Optimization of Ensemble Kernels for Sales Prediction with Gaussian Process Models
by: Mirshekari, Shahin, et al.
Published: (2024)

Towards Efficient Disaster Response via Cost-effective Unbiased Class Rate Estimation through Neyman Allocation Stratified Sampling Active Learning
by: Bai, Yanbing, et al.
Published: (2024)

Learning Bayesian Networks with Heterogeneous Agronomic Data Sets via Mixed-Effect Models and Hierarchical Clustering
by: Valleggi, Lorenzo, et al.
Published: (2023)

Super-Level-Set Regression: Conditional Quantiles via Volume Minimization
by: Braun, Sacha, et al.
Published: (2026)

Biases in Expected Goals Models Confound Finishing Ability
by: Davis, Jesse, et al.
Published: (2024)

Multi-Fidelity Quantile Regression
by: Liu, Yixiang, et al.
Published: (2026)

Ranking Policy Learning via Marketplace Expected Value Estimation From Observational Data
by: Ebrahimzadeh, Ehsan, et al.
Published: (2024)

Symbolic Quantile Regression for the Interpretable Prediction of Conditional Quantiles
by: Hoekstra, Cas Oude, et al.
Published: (2025)

Bayesian Quantile Regression with Subset Selection: A Decision Analysis Perspective
by: Feldman, Joseph, et al.
Published: (2023)

Bayesian Safety Validation for Failure Probability Estimation of Black-Box Systems
by: Moss, Robert J., et al.
Published: (2023)

Feature Impact Analysis on Top Long-Jump Performances with Quantile Random Forest and Explainable AI Techniques
by: Gan, Qi, et al.
Published: (2025)

Anomaly detection using data depth: multivariate case
by: Mozharovskyi, Pavlo, et al.
Published: (2022)

Bayesian Hybrid Machine Learning of Gallstone Risk
by: Chakraborty, Chitradipa, et al.
Published: (2025)

Neural Networks for Extreme Quantile Regression with an Application to Forecasting of Flood Risk
by: Pasche, Olivier C., et al.
Published: (2022)

A Bayesian Regression Approach for Estimating the Impact of COVID-19 on Consumer Behavior in the Restaurant Industry
by: Hinduja, H., et al.
Published: (2024)

Active Learning For Repairable Hardware Systems With Partial Coverage
by: Potter, Michael, et al.
Published: (2025)

Gaussian Copula Models for Nonignorable Missing Data Using Auxiliary Marginal Quantiles
by: Feldman, Joseph, et al.
Published: (2024)

Predictive Scale-Bridging Simulations through Active Learning
by: Karra, Satish, et al.
Published: (2022)

Interval Prediction of Annual Average Daily Traffic on Local Roads via Quantile Random Forest with High-Dimensional Spatial Data
by: Yao, Ying, et al.
Published: (2025)

Sparse Bayesian Deep Functional Learning with Structured Region Selection
by: Zhu, Xiaoxian, et al.
Published: (2026)

A Deep Bayesian Nonparametric Framework for Robust Mutual Information Estimation
by: Fazeliasl, Forough, et al.
Published: (2025)

What is in a Price? Estimating Willingness-to-Pay with Bayesian Hierarchical Models
by: Pillai, Srijesh, et al.
Published: (2025)

Differentially Private Conformal Prediction via Quantile Binary Search
by: Romanus, Ogonnaya M., et al.
Published: (2025)

Bayesian Deep Learning for Discrete Choice
by: Villarraga, Daniel F., et al.
Published: (2025)

Spatially-Heterogeneous Causal Bayesian Networks for Seismic Multi-Hazard Estimation: A Variational Approach with Gaussian Processes and Normalizing Flows
by: Li, Xuechun, et al.
Published: (2025)

Bayesian Deployment Approval for Learned Landing Controllers under Finite Rollout Validation
by: Jiang, Fei, et al.
Published: (2026)

Learning Car-Following Behaviors Using Bayesian Matrix Normal Mixture Regression
by: Zhang, Chengyuan, et al.
Published: (2024)

Isotonic Quantile Regression Averaging for uncertainty quantification of electricity price forecasts
by: Lipiecki, Arkadiusz, et al.
Published: (2025)

Integration of Active Learning and MCMC Sampling for Efficient Bayesian Calibration of Mechanical Properties
by: Riccius, Leon, et al.
Published: (2024)

Integrating Response Time and Attention Duration in Bayesian Preference Learning for Multiple Criteria Decision Aiding
by: Jiang, Jiaxuan, et al.
Published: (2025)

Distributional Regression U-Nets for the Postprocessing of Precipitation Ensemble Forecasts
by: Pic, Romain, et al.
Published: (2024)

Bayesian algorithmic perfumery: A Hierarchical Relevance Vector Machine for the Estimation of Personalized Fragrance Preferences based on Three Sensory Layers and Jungian Personality Archetypes
by: Martinez, Rolando Gonzales
Published: (2024)

Singular Bayesian Neural Networks
by: Toure, Mame Diarra, et al.
Published: (2026)

Absolute Risk Prediction for Cannabis Use Disorder in Adolescence and Early Adulthood Using Bayesian Machine Learning
by: Wang, Tingfang, et al.
Published: (2025)