Contextual Discounting of Belief Functions. - David Mercier; Benjamin Quost; Thierry Denoeux (ECSQARU, 2005)

Pairwise classifier combination using belief functions. - Benjamin Quost; Thierry Denoeux; Marie-Hélène Masson (Pattern Recognit. Lett., 2007)

Refined classifier combination using belief functions. - Benjamin Quost; Marie-Hélène Masson; Thierry Denoeux (FUSION, 2008)

Refined modeling of sensor reliability in the belief function framework using contextual discounting. - David Mercier; Benjamin Quost; Thierry Denoeux (Inf. Fusion, 2008)

Learning from data with uncertain labels by boosting credal classifiers. - Benjamin Quost; Thierry Denoeux (KDD Workshop on Knowledge Discovery from Uncertain Data, 2009)

CECM: Adding pairwise constraints to evidential clustering. - Violaine Antoine; Benjamin Quost; Marie-Hélène Masson; Thierry Denoeux (FUZZ-IEEE, 2010)

Clustering Fuzzy Data Using the Fuzzy EM Algorithm. - Benjamin Quost; Thierry Denoeux (SUM, 2010)

CEVCLUS: Constrained evidential clustering of proximity data. - Violaine Antoine; Benjamin Quost; Mylène Masson; Thierry Denoeux (EUSFLAT Conf., 2011)

Combining Binary Classifiers with Imprecise Probabilities. - Sébastien Destercke; Benjamin Quost (IUKM, 2011)

Classifier fusion in the Dempster-Shafer framework using optimized t-norm based combination rules. - Benjamin Quost; Marie-Hélène Masson; Thierry Denoeux (Int. J. Approx. Reason., 2011)

Correcting Binary Imprecise Classifiers: Local vs Global Approach. - Sébastien Destercke; Benjamin Quost (SUM, 2012)

CECM: Constrained evidential C-means algorithm. - Violaine Antoine; Benjamin Quost; Marie-Hélène Masson; Thierry Denoeux (Comput. Stat. Data Anal., 2012)

Sound Source Localization from Uncertain Information Using the Evidential EM Algorithm. - Xun Wang 002; Benjamin Quost; Jean-Daniel Chazot; Jérôme Antoni (SUM, 2013)

Logistic Regression of Soft Labeled Instances via the Evidential EM Algorithm. - Benjamin Quost (Belief Functions, 2014)

Soft label based semi-supervised boosting for classification and object recognition. - Dingfu Zhou; Benjamin Quost; Vincent Frémont (ICARCV, 2014)

On modeling ego-motion uncertainty for moving object detection from a mobile platform. - Dingfu Zhou; Vincent Frémont; Benjamin Quost; Bihao Wang (Intelligent Vehicles Symposium, 2014)

Editorial. - Marie-Hélène Masson; Sébastien Destercke; Benjamin Quost (Int. J. Approx. Reason., 2014)

CEVCLUS: evidential clustering with instance-level constraints for relational data. - Violaine Antoine; Benjamin Quost; Marie-Hélène Masson; Thierry Denoeux (Soft Comput., 2014)

Estimating energy consumption of a PHEV using vehicle and on-board navigation data. - Abdel-Djalil Ourabah; Benjamin Quost; Atef Gayed; Thierry Denoeux (Intelligent Vehicles Symposium, 2015)

Clustering and classification of fuzzy data using the fuzzy EM algorithm. - Benjamin Quost; Thierry Denoeux (Fuzzy Sets Syst., 2016)

Parametric classification with soft labels using the evidential EM algorithm: linear discriminant analysis versus logistic regression. - Benjamin Quost; Thierry Denoeux; Shoumei Li (Adv. Data Anal. Classif., 2017)

Moving object detection and segmentation in urban environments from a moving platform. - Dingfu Zhou; Vincent Frémont; Benjamin Quost; Yuchao Dai; Hongdong Li (Image Vis. Comput., 2017)

Classification by pairwise coupling of imprecise probabilities. - Benjamin Quost; Sébastien Destercke (Pattern Recognit., 2018)

Dealing with Atypical Instances in Evidential Decision-Making. - Benjamin Quost; Marie-Hélène Masson; Sébastien Destercke (SUM, 2020)

Cautious relational clustering: A thresholding approach. - Marie-Hélène Masson; Benjamin Quost; Sébastien Destercke (Expert Syst. Appl., 2020)

Decision-making from Partial Instances by Active Feature Querying. - Benjamin Quost (ISIPTA, 2021)

Cautious Random Forests: a New Decision Strategy and some Experiments. - Haifei Zhang; Benjamin Quost; Marie-Hélène Masson (ISIPTA, 2021)

A Robust Bayesian Estimation Approach for the Imprecise Plackett-Luce Model. - Tathagata Basu; Sébastien Destercke; Benjamin Quost (IPMU (1), 2022)

Vehicle consumption estimation via calibrated Gaussian Process regression. - Mathieu Randon; Benjamin Quost; Nassim Boudaoud; Dirk von Wissel (IV, 2022)

Explications contrefactuelles pour les forêts aléatoires prudentes. - Haifei Zhang; Benjamin Quost; Marie-Hélène Masson (LFA, 2022)

Forêts aléatoires prudentes : une nouvelle stratégie de décision et quelques expériences. - Haifei Zhang; Benjamin Quost; Marie-Hélène Masson (LFA, 2022)

Self Learning using Venn-Abers predictors. - Come Rodriguez; Vitor Martin Bordini; Sébastien Destercke; Benjamin Quost (COPA, 2023)

Cautious Decision-Making for Tree Ensembles. - Haifei Zhang; Benjamin Quost; Marie-Hélène Masson (ECSQARU, 2023)

Learning calibrated belief functions from conformal predictions. - Vitor Martin Bordini; Sébastien Destercke; Benjamin Quost (ISIPTA, 2023)

Robust Consumption Planning from Uncertain Power Demand Predictions. - Mathieu Randon; Benjamin Quost; Dirk von Wissel; Nassim Boudaoud (IV, 2023)

Cautious weighted random forests. - Haifei Zhang; Benjamin Quost; Marie-Hélène Masson (Expert Syst. Appl., 2023)

Geospatial Uncertainties: A Focus on Intervals and Spatial Models Based on Inverse Distance Weighting. - Priscillia Labourg; Sébastien Destercke; Romain Guillaume; Jérémy Rohmer 001; Benjamin Quost; Stéphane Belbèze (IPMU (1), 2024)

Probabilistic Circuits with Constraints via Convex Optimization. - Soroush Ghandi; Benjamin Quost; Cassio de Campos (ECML/PKDD (3), 2024)

Robust Discrete Bayesian Classifier Under Covariate and Label Noise. - Wenlong Chen; Cyprien Gilet; Benjamin Quost; Sébastien Destercke (SUM, 2024)

Inferring from an imprecise Plackett-Luce model: Application to label ranking. - Loïc Adam; Arthur Van Camp; Sébastien Destercke; Benjamin Quost (Fuzzy Sets Syst., 2024)

Deep reinforcement learning with predictive auxiliary task for autonomous train collision avoidance. - Antoine Plissonneau; Luca Jourdan; Damien Trentesaux; Lotfi Abdi; Mohamed Sallak; Abdelghani Bekrar; Benjamin Quost; Walter Schön (J. Rail Transp. Plan. Manag., 2024)

Imposing Constraints in Probabilistic Circuits via Gradient Optimization. - Soroush Ghandi; Benjamin Quost; Cassio de Campos (IDA, 2025)

Credal discrete classifier. - Wenlong Chen; Cyprien Gilet; Benjamin Quost; Sébastien Destercke (ISIPTA, 2025)

Soft learning probabilistic circuits. - Soroush Ghandi; Benjamin Quost; Cassio P. de Campos (Int. J. Approx. Reason., 2025)

Cautious classifier ensembles for set-valued decision-making. - Haifei Zhang; Benjamin Quost; Marie-Hélène Masson (Int. J. Approx. Reason., 2025)

Reducing Aleatoric and Epistemic Uncertainty through Multi-modal Data Acquisition. - Arthur Hoarau; Benjamin Quost; Sébastien Destercke; Willem Waegeman (CoRR, 2025)