Initializing back propagation networks with prototypes. - Thierry Denoeux; Régis Lengellé (Neural Networks, 1993)

An Adaptive k-NN Rule Based on Dempster-Shafer Theory. - Lalla Merieme Zouhal; Thierry Denoeux (CAIP, 1995)

Performance analysis of a MLP weight initialization algorithm. - Mohamed Karouia; Régis Lengellé; Thierry Denoeux (ESANN, 1995)

Comparison of dynamic feature map models for environmental monitoring. - T. Trautmann; Thierry Denoeux (ICNN, 1995)

Analysis of Rainfall Forecasting using Neural Networks. - Thierry Denoeux; P. Rizand (Neural Comput. Appl., 1995)

A k-nearest neighbor classification rule based on Dempster-Shafer theory. - Thierry Denoeux (IEEE Trans. Syst. Man Cybern., 1995)

Training MLPs layer by layer using an objective function for internal representations. - Régis Lengellé; Thierry Denoeux (Neural Networks, 1996)

Function approximation in the framework of evidence theory: a connectionist approach. - Thierry Denoeux (ICNN, 1997)

Analysis of evidence-theoretic decision rules for pattern classification. - Thierry Denoeux (Pattern Recognit., 1997)

An evidence-theoretic k-NN rule with parameter optimization. - Lalla Merieme Zouhal; Thierry Denoeux (IEEE Trans. Syst. Man Cybern. Part C, 1998)

Handling Different Forms of Uncertainty in Regression Analysis: A Fuzzy Belief Structure Approach. - Simon Petit-Renaud; Thierry Denoeux (ESCQARU, 1999)

State Recognition in Discrete Dynamical Systems Using Petri Nets and Evidence Theory. - Michèle Rombaut; Iman Jarkass; Thierry Denoeux (ESCQARU, 1999)

An hybrid neural network based system for optimization of coagulant dosing in a water treatment plant. - Nicolas Valentin; Thierry Denoeux; F. Fotoohi (IJCNN, 1999)

Reasoning with imprecise belief structures. - Thierry Denoeux (Int. J. Approx. Reason., 1999)

Induction of decision trees from partially classified data using belief functions. - Thierry Denoeux; M. Skarstein Bjanger (SMC, 2000)

Modeling vague beliefs using fuzzy-valued belief structures. - Thierry Denoeux (Fuzzy Sets Syst., 2000)

Multidimensional scaling of interval-valued dissimilarity data. - Thierry Denoeux; Marie-Hélène Masson (Pattern Recognit. Lett., 2000)

A neural network classifier based on Dempster-Shafer theory. - Thierry Denoeux (IEEE Trans. Syst. Man Cybern. Part A, 2000)

Coarsening Approximations of Belief Functions. - Amel Ben Yaghlane; Thierry Denoeux; Khaled Mellouli (ECSQARU, 2001)

Likelihood-based Vs Distance-based Evidential Classifiers. - Patrick Vannoorenberghe; Thierry Denoeux (FUZZ-IEEE, 2001)

Handling possibilistic labels in pattern classification using evidential reasoning. - Thierry Denoeux; Lalla Merieme Zouhal (Fuzzy Sets Syst., 2001)

A neural network-based software sensor for coagulation control in a water treatment plant. - Nicolas Valentin; Thierry Denoeux (Intell. Data Anal., 2001)

Inner and Outer Approximation of Belief Structures Using a Hierarchical Clustering Approach. - Thierry Denoeux (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2001)

Multidimensional scaling of fuzzy dissimilarity data. - Marie-Hélène Masson; Thierry Denoeux (Fuzzy Sets Syst., 2002)

Approximating the combination of belief functions using the fast Mo"bius transform in a coarsened frame. - Thierry Denoeux; Amel Ben Yaghlane (Int. J. Approx. Reason., 2002)

Risk Assessment in Drinking Water Production Using Belief Functions. - Sabrina Démotier; Thierry Denoeux; Paul Walter Schön (ECSQARU, 2003)

A new approach to assess risk in water treatment using the belief function framework. - Sabrina Démotier; Paul Walter Schön; Thierry Denoeux; Khaled Odeh (SMC, 2003)

Resample and combine: an approach to improving uncertainty representation in evidential pattern classification. - Jérémie François; Yves Grandvalet; Thierry Denoeux; Jean-Michel Roger (Inf. Fusion, 2003)

Addendum to resample and combine: an approach to improving uncertainty representation in evidential pattern classification. - Jérémie François; Yves Grandvalet; Thierry Denoeux; Jean-Michel Roger (Inf. Fusion, 2003)

Recycling experiments for sludge monitoring in waste water treatment. - Sandro Glaucio Maquiné de Souza; Thierry Denoeux; Yves Grandvalet (SMC (2), 2004)

Nonparametric regression analysis of uncertain and imprecise data using belief functions. - Simon Petit-Renaud; Thierry Denoeux (Int. J. Approx. Reason., 2004)

Clustering interval-valued proximity data using belief functions. - Marie-Hélène Masson; Thierry Denoeux (Pattern Recognit. Lett., 2004)

Principal component analysis of fuzzy data using autoassociative neural networks. - Thierry Denoeux; Marie-Hélène Masson (IEEE Trans. Fuzzy Syst., 2004)

EVCLUS: evidential clustering of proximity data. - Thierry Denoeux; Marie-Hélène Masson (IEEE Trans. Syst. Man Cybern. Part B, 2004)

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

R. P. Srivastava and T. J. Mock, Belief Functions in Business Decisions, in Studies in Fuzziness and Soft Computing, vol. 88, Physica-Verlag, Heidelberg (2002) ISBN 3-7908-1451-2 (345pp.) - Thierry Denoeux (Fuzzy Sets Syst., 2005)

Nonparametric rank-based statistics and significance tests for fuzzy data. - Thierry Denoeux; Marie-Hélène Masson; Pierre-Alexandre Hébert (Fuzzy Sets Syst., 2005)

Editorial. - Thierry Denoeux; Piero P. Bonissone (Int. J. Approx. Reason., 2005)

Output coding of spatially dependent subclassifiers in evidential framework. Application to the diagnosis of railway track/vehicle transmission system. - Alexandra Debiolles; Latifa Oukhellou; Thierry Denoeux; Patrice Aknin (FUSION, 2006)

The cautious rule of combination for belief functions and some extensions. - Thierry Denoeux (FUSION, 2006)

General Correction Mechanisms for Weakening or Reinforcing Belief Functions. - David Mercier; Thierry Denoeux; Marie-Hélène Masson (FUSION, 2006)

Fuzzy multidimensional scaling. - Pierre-Alexandre Hébert; Marie-Hélène Masson; Thierry Denoeux (Comput. Stat. Data Anal., 2006)

In Memoriam: Philippe Smets (1938-2005). - Hugues Bersini; Thierry Denoeux; Didier Dubois; Henri Prade (Fuzzy Sets Syst., 2006)

Inferring a possibility distribution from empirical data. - Marie-Hélène Masson; Thierry Denoeux (Fuzzy Sets Syst., 2006)

Philippe Smets (1938-2005). - Hugues Bersini; Thierry Denoeux; Didier Dubois; Henri Prade (Int. J. Approx. Reason., 2006)

Constructing belief functions from sample data using multinomial confidence regions. - Thierry Denoeux (Int. J. Approx. Reason., 2006)

Risk assessment based on weak information using belief functions: a case study in water treatment. - Sabrina Démotier; Paul Walter Schön; Thierry Denoeux (IEEE Trans. Syst. Man Cybern. Syst., 2006)

Classification Using Belief Functions: Relationship Between Case-Based and Model-Based Approaches. - Thierry Denoeux; Philippe Smets (IEEE Trans. Syst. Man Cybern. Part B, 2006)

Consonant Belief Function Induced by a Confidence Set of Pignistic Probabilities. - Astride Aregui; Thierry Denoeux (ECSQARU, 2007)

Pattern Recognition and Information Fusion Using Belief Functions: Some Recent Developments. - Thierry Denoeux (ECSQARU, 2007)

On Latent Belief Structures. - Frédéric Pichon; Thierry Denoeux (ECSQARU, 2007)

Fusion of one-class classifiers in the belief function framework. - Astride Aregui; Thierry Denoeux (FUSION, 2007)

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

Multi-label classification algorithm derived from K-nearest neighbor rule with label dependencies. - Zoulficar Younes; Fahed Abdallah; Thierry Denoeux (EUSIPCO, 2008)

A New Justification of the Unnormalized Dempster's Rule of Combination from the Least Commitment Principle. - Frédéric Pichon; Thierry Denoeux (FLAIRS, 2008)

Distributed data fusion: application to confidence management in vehicular networks. - Véronique Cherfaoui; Thierry Denoeux; Zohra Leila Cherfi (FUSION, 2008)

Map matching algorithm using belief function theory. - Ghalia Nassreddine; Fahed Abdallah; Thierry Denoeux (FUSION, 2008)

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

Mixture Model Estimation with Soft Labels. - Etienne Côme; Latifa Oukhellou; Thierry Denoeux; Patrice Aknin (SMPS, 2008)

Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence. - Thierry Denoeux (Artif. Intell., 2008)

Constructing consonant belief functions from sample data using confidence sets of pignistic probabilities. - Astride Aregui; Thierry Denoeux (Int. J. Approx. Reason., 2008)

Special issue in memory of Philippe Smets (1938-2005). - Thierry Denoeux (Int. J. Approx. Reason., 2008)

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

ECM: An evidential version of the fuzzy c. - Marie-Hélène Masson; Thierry Denoeux (Pattern Recognit., 2008)

A k -Nearest Neighbor Classification Rule Based on Dempster-Shafer Theory. - Thierry Denoeux (Classic Works of the Dempster-Shafer Theory of Belief Functions, 2008)

Belief Functions and Cluster Ensembles. - Marie-Hélène Masson; Thierry Denoeux (ECSQARU, 2009)

Partially-supervised learning in Independent Factor Analysis. - Etienne Côme; Latifa Oukhellou; Patrice Aknin; Thierry Denoeux (ESANN, 2009)

Fuzzy Modelling of Sensor Data for the Estimation of an Origin-Destination Matrix. - Krystyna Biletska; Sophie Midenet; Marie-Hélène Masson; Thierry Denoeux (IFSA/EUSFLAT Conf., 2009)

A state estimation method for multiple model systems using belief function theory. - Ghalia Nassreddine; Fahed Abdallah; Thierry Denoeux (FUSION, 2009)

Noiseless Independent Factor Analysis with Mixing Constraints in a Semi-supervised Framework. Application to Railway Device Fault Diagnosis. - Etienne Côme; Latifa Oukhellou; Thierry Denoeux; Patrice Aknin (ICANN (2), 2009)

Short-time OD matrix estimation for a complex junction using fuzzy-timed high-level petri nets. - Krystyna Biletska; Marie-Hélène Masson; Sophie Midenet; Thierry Denoeux (ITSC, 2009)

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

Multisensor data fusion for OD matrix estimation. - Krystyna Biletska; Marie-Hélène Masson; Sophie Midenet; Thierry Denoeux (SMC, 2009)

An Evidence-Theoretic k-Nearest Neighbor Rule for Multi-label Classification. - Zoulficar Younes; Fahed Abdallah; Thierry Denoeux (SUM, 2009)

Decision fusion for postal address recognition using belief functions. - David Mercier; Genevieve Cron; Thierry Denoeux; Marie-Hélène Masson (Expert Syst. Appl., 2009)

Extending stochastic ordering to belief functions on the real line. - Thierry Denoeux (Inf. Sci., 2009)

Learning from partially supervised data using mixture models and belief functions. - Etienne Côme; Latifa Oukhellou; Thierry Denoeux; Patrice Aknin (Pattern Recognit., 2009)

RECM: Relational evidential c-means algorithm. - Marie-Hélène Masson; Thierry Denoeux (Pattern Recognit. Lett., 2009)

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

Fuzzy multi-label learning under veristic variables. - Zoulficar Younes; Fahed Abdallah; Thierry Denoeux (FUZZ-IEEE, 2010)

Evidential Multi-Label Classification Approach to Learning from Data with Imprecise Labels. - Zoulficar Younes; Fahed Abdallah; Thierry Denoeux (IPMU, 2010)

Dempster-Shafer Reasoning in Large Partially Ordered Sets: Applications in Machine Learning. - Thierry Denoeux; Marie-Hélène Masson (IUM, 2010)

Theory of Belief Functions for Data Analysis and Machine Learning Applications: Review and Prospects. - Thierry Denoeux (KSEM, 2010)

Maximum Likelihood from Evidential Data: An Extension of the EM Algorithm. - Thierry Denoeux (SMPS, 2010)

Statistical Inference with Belief Functions and Possibility Measures: A Discussion of Basic Assumptions. - Didier Dubois; Thierry Denoeux (SMPS, 2010)

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

Representing uncertainty on set-valued variables using belief functions. - Thierry Denoeux; Zoulficar Younes; Fahed Abdallah (Artif. Intell., 2010)

Fault diagnosis in railway track circuits using Dempster-Shafer classifier fusion. - Latifa Oukhellou; Alexandra Debiolles; Thierry Denoeux; Patrice Aknin (Eng. Appl. Artif. Intell., 2010)

The Unnormalized Dempster's Rule of Combination: A New Justification from the Least Commitment Principle and Some Extensions. - Frédéric Pichon; Thierry Denoeux (J. Autom. Reason., 2010)

State Estimation Using Interval Analysis and Belief-Function Theory: Application to Dynamic Vehicle Localization. - Ghalia Nassreddine; Fahed Abdallah; Thierry Denoeux (IEEE Trans. Syst. Man Cybern. Part B, 2010)

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

Semi-supervised Feature Extraction Using Independent Factor Analysis. - Latifa Oukhellou; Etienne Côme; Patrice Aknin; Thierry Denoeux (ICMLA (2), 2011)

Using Imprecise and Uncertain Information to Enhance the Diagnosis of a Railway Device. - Zohra Leila Cherfi; Latifa Oukhellou; Etienne Côme; Thierry Denoeux; Patrice Aknin (NL-MUA, 2011)

A Dependent Multilabel Classification Method Derived from the k-Nearest Neighbor Rule. - Zoulficar Younes; Fahed Abdallah; Thierry Denoeux; Hichem Snoussi (EURASIP J. Adv. Signal Process., 2011)

Maximum likelihood estimation from fuzzy data using the EM algorithm. - Thierry Denoeux (Fuzzy Sets Syst., 2011)

Ensemble clustering in the belief functions framework. - Marie-Hélène Masson; Thierry Denoeux (Int. J. Approx. Reason., 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)

A Multiple-Hypothesis Map-Matching Method Suitable for Weighted and Box-Shaped State Estimation for Localization. - Fahed Abdallah; Ghalia Nassreddine; Thierry Denoeux (IEEE Trans. Intell. Transp. Syst., 2011)

Combining Statistical and Expert Evidence within the D-S Framework: Application to Hydrological Return Level Estimation. - Nadia Ben Abdallah; Nassima Mouhous Voyneau; Thierry Denoeux (Belief Functions, 2012)

Conditioning in Dempster-Shafer Theory: Prediction vs. Revision. - Didier Dubois; Thierry Denoeux (Belief Functions, 2012)

Evidential Multi-label Classification Using the Random k-Label Sets Approach. - Sawsan Kanj; Fahed Abdallah; Thierry Denoeux (Belief Functions, 2012)

Ranking from Pairwise Comparisons in the Belief Functions Framework. - Marie-Hélène Masson; Thierry Denoeux (Belief Functions, 2012)

Partially-Hidden Markov Models. - Emmanuel Ramasso; Thierry Denoeux; Noureddine Zerhouni (Belief Functions, 2012)

Classification Trees Based on Belief Functions. - Nicolas Sutton-Charani; Sébastien Destercke; Thierry Denoeux (Belief Functions, 2012)

Distributed Data Fusion for Detecting Sybil Attacks in VANETs. - Nicole El Zoghby; Véronique Cherfaoui; Bertrand Ducourthial; Thierry Denoeux (Belief Functions, 2012)

Purifying training data to improve performance of multi-label classification algorithms. - Sawsan Kanj; Fahed Abdallah; Thierry Denoeux (FUSION, 2012)

Constructing Rule-Based Models Using the Belief Functions Framework. - Rui Jorge Almeida; Thierry Denoeux; Uzay Kaymak (IPMU (3), 2012)

Self-stabilizing Distributed Data Fusion. - Bertrand Ducourthial; Véronique Cherfaoui; Thierry Denoeux (SSS, 2012)

Evidential reasoning in large partially ordered sets - Application to multi-label classification, ensemble clustering and preference aggregation. - Thierry Denoeux; Marie-Hélène Masson (Ann. Oper. Res., 2012)

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

Relevance and truthfulness in information correction and fusion. - Frédéric Pichon; Didier Dubois; Thierry Denoeux (Int. J. Approx. Reason., 2012)

Fault diagnosis of a railway device using semi-supervised independent factor analysis with mixing constraints. - Etienne Côme; Latifa Oukhellou; Thierry Denoeux; Patrice Aknin (Pattern Anal. Appl., 2012)

Partially supervised Independent Factor Analysis using soft labels elicited from multiple experts: application to railway track circuit diagnosis. - Zohra Leila Cherfi; Latifa Oukhellou; Etienne Côme; Thierry Denoeux; Patrice Aknin (Soft Comput., 2012)

Using Dempster-Shafer theory to model uncertainty in climate change and environmental impact assessments. - Nadia Ben Abdallah; Nassima Mouhous Voyneau; Thierry Denoeux (FUSION, 2013)

Optimal object association from pairwise evidential mass functions. - Nicole El Zoghby; Véronique Cherfaoui; Thierry Denoeux (FUSION, 2013)

Learning Decision Trees from Uncertain Data with an Evidential EM Approach. - Nicolas Sutton-Charani; Sébastien Destercke; Thierry Denoeux (ICMLA (1), 2013)

Evidential Grammars for Image Interpretation - Application to Multimodal Traffic Scene Understanding. - Jean-Baptiste Bordes; Franck Davoine; Philippe Xu; Thierry Denoeux (IUKM, 2013)

Information Fusion on Oversegmented Images: An Application for Urban Scene Understanding. - Philippe Xu; Franck Davoine; Jean-Baptiste Bordes; Huijing Zhao; Thierry Denoeux (MVA, 2013)

Maximum Likelihood Estimation from Uncertain Data in the Belief Function Framework. - Thierry Denoeux (IEEE Trans. Knowl. Data Eng., 2013)

Predicting Stock Returns in the Capital Asset Pricing Model Using Quantile Regression and Belief Functions. - Kittawit Autchariyapanitkul; Somsak Chanaim; Songsak Sriboonchitta; Thierry Denoeux (Belief Functions, 2014)

The Evidence-Theoretic k-NN Rule for Rank-Ordered Data: Application to Predict an Individual's Source of Loan. - Supanika Leurcharusmee; Peerapat Jatukannyaprateep; Songsak Sriboonchitta; Thierry Denoeux (Belief Functions, 2014)

Training and Evaluating Classifiers from Evidential Data: Application to E 2 M Decision Tree Pruning. - Nicolas Sutton-Charani; Sébastien Destercke; Thierry Denoeux (Belief Functions, 2014)

Evidential Logistic Regression for Binary SVM Classifier Calibration. - Philippe Xu; Franck Davoine; Thierry Denoeux (Belief Functions, 2014)

Evidential combination of pedestrian detectors. - Philippe Xu; Franck Davoine; Thierry Denoeux (BMVC, 2014)

Fusion of pairwise nearest-neighbor classifiers based on pairwise-weighted distance metric and Dempster-Shafer theory. - Lianmeng Jiao; Thierry Denoeux; Quan Pan 001 (FUSION, 2014)

Application of E 2 M Decision Trees to Rubber Quality Prediction. - Nicolas Sutton-Charani; Sébastien Destercke; Thierry Denoeux (IPMU (1), 2014)

Evidential distributed dynamic map for cooperative perception in VANets. - Nicole El Zoghby; Véronique Cherfaoui; Thierry Denoeux (Intelligent Vehicles Symposium, 2014)

Special issue on imprecision in statistical data analysis. - Ana Colubi; Thierry Denoeux (Comput. Stat. Data Anal., 2014)

Combining statistical and expert evidence using belief functions: Application to centennial sea level estimation taking into account climate change. - Nadia Ben Abdallah; Nassima Mouhous Voyneau; Thierry Denoeux (Int. J. Approx. Reason., 2014)

Likelihood-based belief function: Justification and some extensions to low-quality data. - Thierry Denoeux (Int. J. Approx. Reason., 2014)

Rejoinder on "Likelihood-based belief function: Justification and some extensions to low-quality data". - Thierry Denoeux (Int. J. Approx. Reason., 2014)

Forecasting using belief functions: An application to marketing econometrics. - Orakanya Kanjanatarakul; Songsak Sriboonchitta; Thierry Denoeux (Int. J. Approx. Reason., 2014)

Fusion of multi-tracer PET images for dose painting. - Benoît Lelandais; Su Ruan; Thierry Denoeux; Pierre Vera; Isabelle Gardin (Medical Image Anal., 2014)

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

Optimal Object Association in the Dempster-Shafer Framework. - Thierry Denoeux; Nicole El Zoghby; Véronique Cherfaoui; Antoine Jouglet (IEEE Trans. Cybern., 2014)

Fusion d'informations pour la compréhension de scènes. - Philippe Xu; Franck Davoine; Jean-Baptiste Bordes; Thierry Denoeux (Traitement du Signal, 2014)

Making Use of Partial Knowledge About Hidden States in HMMs: An Approach Based on Belief Functions. - Emmanuel Ramasso; Thierry Denoeux (IEEE Trans. Fuzzy Syst., 2014)

Evidential Editing K-Nearest Neighbor Classifier. - Lianmeng Jiao; Thierry Denoeux; Quan Pan 001 (ECSQARU, 2015)

Evidential multinomial logistic regression for multiclass classifier calibration. - Philippe Xu; Franck Davoine; Thierry Denoeux (FUSION, 2015)

Outcome prediction in tumour therapy based on Dempster-Shafer theory. - Chunfeng Lian; Su Ruan; Thierry Denoeux; Pierre Vera (ISBI, 2015)

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)

Dempster-Shafer Theory Based Feature Selection with Sparse Constraint for Outcome Prediction in Cancer Therapy. - Chunfeng Lian; Su Ruan; Thierry Denoeux; Hua Li 003; Pierre Vera (MICCAI (3), 2015)

Modeling dependence between error components of the stochastic frontier model using copula: Application to intercrop coffee production in Northern Thailand. - Aree Wiboonpongse; Jianxu Liu; Songsak Sriboonchitta; Thierry Denoeux (Int. J. Approx. Reason., 2015)

Interval-Valued Linear Model. - Xun Wang 002; Shoumei Li; Thierry Denoeux (Int. J. Comput. Intell. Syst., 2015)

Belief rule-based classification system: Extension of FRBCS in belief functions framework. - Lianmeng Jiao; Quan Pan 001; Thierry Denoeux; Yan Liang 001; Xiaoxue Feng (Inf. Sci., 2015)

EK-NNclus: A clustering procedure based on the evidential K-nearest neighbor rule. - Thierry Denoeux; Orakanya Kanjanatarakul; Songsak Sriboonchitta (Knowl. Based Syst., 2015)

An evidential classifier based on feature selection and two-step classification strategy. - Chunfeng Lian; Su Ruan; Thierry Denoeux (Pattern Recognit., 2015)

Estimation and Prediction Using Belief Functions: Application to Stochastic Frontier Analysis. - Orakanya Kanjanatarakul; Nachatchapong Kaewsompong; Songsak Sriboonchitta; Thierry Denoeux (Econometrics of Risk, 2015)

The Classifier Chain Generalized Maximum Entropy Model for Multi-label Choice Problems. - Supanika Leurcharusmee; Jirakom Sirisrisakulchai; Songsak Sriboonchitta; Thierry Denoeux (Econometrics of Risk, 2015)

k-EVCLUS: Clustering Large Dissimilarity Data in the Belief Function Framework. - Orakanya Kanjanatarakul; Songsak Sriboonchitta; Thierry Denoeux (BELIEF, 2016)

Identification of Elastic Properties Based on Belief Function Inference. - Liqi Sui; Pierre Feissel; Thierry Denoeux (BELIEF, 2016)

Joint Feature Transformation and Selection Based on Dempster-Shafer Theory. - Chunfeng Lian; Su Ruan; Thierry Denoeux (IPMU (1), 2016)

Evidential Clustering: A Review. - Thierry Denoeux; Orakanya Kanjanatarakul (IUKM, 2016)

Robust Cancer Treatment Outcome Prediction Dealing with Small-Sized and Imbalanced Data from FDG-PET Images. - Chunfeng Lian; Su Ruan; Thierry Denoeux; Hua Li 003; Pierre Vera (MICCAI (2), 2016)

Beyond Fuzzy, Possibilistic and Rough: An Investigation of Belief Functions in Clustering. - Thierry Denoeux; Orakanya Kanjanatarakul (SMPS, 2016)

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

40 years of Dempster-Shafer theory. - Thierry Denoeux (Int. J. Approx. Reason., 2016)

Prediction of future observations using belief functions: A likelihood-based approach. - Orakanya Kanjanatarakul; Thierry Denoeux; Songsak Sriboonchitta (Int. J. Approx. Reason., 2016)

Evidential calibration of binary SVM classifiers. - Philippe Xu; Franck Davoine; Hongbin Zha; Thierry Denoeux (Int. J. Approx. Reason., 2016)

Evidential clustering of large dissimilarity data. - Thierry Denoeux; Songsak Sriboonchitta; Orakanya Kanjanatarakul (Knowl. Based Syst., 2016)

Selecting radiomic features from FDG-PET images for cancer treatment outcome prediction. - Chunfeng Lian; Su Ruan; Thierry Denoeux; Fabrice Jardin; Pierre Vera (Medical Image Anal., 2016)

Multimodal information fusion for urban scene understanding. - Philippe Xu; Franck Davoine; Jean-Baptiste Bordes; Huijing Zhao; Thierry Denoeux (Mach. Vis. Appl., 2016)

Editing training data for multi-label classification with the k-nearest neighbor rule. - Sawsan Kanj; Fahed Abdallah; Thierry Denoeux; Kifah Tout (Pattern Anal. Appl., 2016)

Modelling and predicting partial orders from pairwise belief functions. - Marie-Hélène Masson; Sébastien Destercke; Thierry Denoeux (Soft Comput., 2016)

Dissimilarity Metric Learning in the Belief Function Framework. - Chunfeng Lian; Su Ruan; Thierry Denoeux (IEEE Trans. Fuzzy Syst., 2016)

A Hybrid Belief Rule-Based Classification System Based on Uncertain Training Data and Expert Knowledge. - Lianmeng Jiao; Thierry Denoeux; Quan Pan 001 (IEEE Trans. Syst. Man Cybern. Syst., 2016)

Constrained interval-valued linear regression model. - Feng Li; Shoumei Li; Nana Tang; Thierry Denoeux (FUSION, 2017)

Accurate tumor segmentation in FDG-PET images with guidance of complementary CT images. - Chunfeng Lian; Su Ruan; Thierry Denoeux; Yu Guo; Pierre Vera (ICIP, 2017)

Tumor delineation in FDG-PET images using a new evidential clustering algorithm with spatial regularization and adaptive distance metric. - Chunfeng Lian; Su Ruan; Thierry Denoeux; Hua Li 003; Pierre Vera (ISBI, 2017)

Distributed data fusion in the dempster-shafer framework. - Orakanya Kanjanatarakul; Thierry Denoeux (SoSE, 2017)

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)

Evidential grammars: A compositional approach for scene understanding. Application to multimodal street data. - Jean-Baptiste Bordes; Franck Davoine; Philippe Xu; Thierry Denoeux (Appl. Soft Comput., 2017)

A double-copula stochastic frontier model with dependent error components and correction for sample selection. - Songsak Sriboonchitta; Jianxu Liu; Aree Wiboonpongse; Thierry Denoeux (Int. J. Approx. Reason., 2017)

Logistic Regression Revisited: Belief Function Analysis. - Thierry Denoeux (BELIEF, 2018)

An Evidential K-Nearest Neighbor Classifier Based on Contextual Discounting and Likelihood Maximization. - Orakanya Kanjanatarakul; Siwarat Kuson; Thierry Denoeux (BELIEF, 2018)

Frequency-calibrated belief functions: Review and new insights. - Thierry Denoeux; Shoumei Li (Int. J. Approx. Reason., 2018)

Identification of elastic properties in the belief function framework. - Liqi Sui; Pierre Feissel; Thierry Denoeux (Int. J. Approx. Reason., 2018)

k-CEVCLUS: Constrained evidential clustering of large dissimilarity data. - Feng Li; Shoumei Li; Thierry Denoeux (Knowl. Based Syst., 2018)

Evidential K-NN classification with enhanced performance via optimizing a class of parametric conjunctive t-rules. - Zhi-gang Su; Thierry Denoeux; Yong-sheng Hao; Ming Zhao (Knowl. Based Syst., 2018)

Spatial Evidential Clustering With Adaptive Distance Metric for Tumor Segmentation in FDG-PET Images. - Chunfeng Lian; Su Ruan; Thierry Denoeux; Hua Li 003; Pierre Vera (IEEE Trans. Biomed. Eng., 2018)

Evaluating and Comparing Soft Partitions: An Approach Based on Dempster-Shafer Theory. - Thierry Denoeux; Shoumei Li; Songsak Sriboonchitta (IEEE Trans. Fuzzy Syst., 2018)

Quantifying Predictive Uncertainty Using Belief Functions: Different Approaches and Practical Construction. - Thierry Denoeux (Predictive Econometrics and Big Data, 2018)

Quality of Information Sources in Information Fusion. - Frédéric Pichon; Didier Dubois; Thierry Denoeux (Information Quality in Information Fusion and Decision Making, 2019)

Multistep Prediction using Point-Cloud Approximation of Continuous Belief Functions. - Thierry Denoeux; Orakanya Kanjanatarakul (FUZZ-IEEE, 2019)

Collaborative Evidential Clustering. - Yixuan Qiao; Shoumei Li; Thierry Denoeux (IFSA/NAFIPS, 2019)

An Axiomatic Utility Theory for Dempster-Shafer Belief Functions. - Thierry Denoeux; Prakash P. Shenoy (ISIPTA, 2019)

Making Set-Valued Predictions in Evidential Classification: A Comparison of Different Approaches. - Liyao Ma; Thierry Denoeux (ISIPTA, 2019)

ConvNet and Dempster-Shafer Theory for Object Recognition. - Zheng Tong; Philippe Xu; Thierry Denoeux (SUM, 2019)

Editorial: Opening up computer science. - Thierry Denoeux (Array, 2019)

From Shallow to Deep Interactions Between Knowledge Representation, Reasoning and Machine Learning (Kay R. Amel group). - Zied Bouraoui; Antoine Cornuéjols; Thierry Denoeux; Sébastien Destercke; Didier Dubois; Romain Guillaume; João Marques-Silva 001; Jérôme Mengin; Henri Prade; Steven Schockaert; Mathieu Serrurier; Christel Vrain (CoRR, 2019)

Decision-making with belief functions: A review. - Thierry Denoeux (Int. J. Approx. Reason., 2019)

A new evidential K-nearest neighbor rule based on contextual discounting with partially supervised learning. - Thierry Denoeux; Orakanya Kanjanatarakul; Songsak Sriboonchitta (Int. J. Approx. Reason., 2019)

Logistic regression, neural networks and Dempster-Shafer theory: A new perspective. - Thierry Denoeux (Knowl. Based Syst., 2019)

BPEC: Belief-Peaks Evidential Clustering. - Zhi-gang Su; Thierry Denoeux (IEEE Trans. Fuzzy Syst., 2019)

Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions. - Chunfeng Lian; Su Ruan; Thierry Denoeux; Hua Li 003; Pierre Vera (IEEE Trans. Image Process., 2019)

Representations of Uncertainty in Artificial Intelligence: Probability and Possibility. - Thierry Denoeux; Didier Dubois; Henri Prade (A Guided Tour of Artificial Intelligence Research (1) (I), 2020)

Representations of Uncertainty in AI: Beyond Probability and Possibility. - Thierry Denoeux; Didier Dubois; Henri Prade (A Guided Tour of Artificial Intelligence Research (1) (I), 2020)

Evidential Deep Neural Networks for Uncertain Data Classification. - Bin Yuan; Xiaodong Yue; Ying Lv; Thierry Denoeux (KSEM (2), 2020)

Combining clusterings in the belief function framework. - Feng Li; Shoumei Li; Thierry Denoeux (Array, 2020)

Belief functions induced by random fuzzy sets: Application to statistical inference. - Thierry Denoeux (CoRR, 2020)

An interval-valued utility theory for decision making with Dempster-Shafer belief functions. - Thierry Denoeux; Prakash P. Shenoy (Int. J. Approx. Reason., 2020)

Calibrated model-based evidential clustering using bootstrapping. - Thierry Denoeux (Inf. Sci., 2020)

Evidential Segmentation of 3D PET/CT Images. - Ling Huang 003; Su Ruan; Pierre Decazes; Thierry Denoeux (BELIEF, 2021)

Fusion of Evidential CNN Classifiers for Image Classification. - Zheng Tong; Philippe Xu; Thierry Denoeux (BELIEF, 2021)

Covid-19 Classification with Deep Neural Network and Belief Functions. - Ling Huang 003; Su Ruan; Thierry Denoeux (BIBE, 2021)

Deep Neural Networks with Prior Evidence for Bladder Cancer Staging. - Xiaoqian Zhou; Xiaodong Yue; Zhikang Xu; Thierry Denoeux; Yufei Chen 002 (BIBM, 2021)

Belief Function-Based Semi-Supervised Learning For Brain Tumor Segmentation. - Ling Huang 003; Su Ruan; Thierry Denoeux (ISBI, 2021)

Deep PET/CT Fusion with Dempster-Shafer Theory for Lymphoma Segmentation. - Ling Huang 003; Thierry Denoeux; David Tonnelet; Pierre Decazes; Su Ruan (MLMI@MICCAI, 2021)

Evidential fully convolutional network for semantic segmentation. - Zheng Tong; Philippe Xu; Thierry Denoeux (Appl. Intell., 2021)

Clustering acoustic emission data streams with sequentially appearing clusters using mixture models. - Emmanuel Ramasso; Thierry Denoeux; Gaël Chevallier (CoRR, 2021)

Belief functions induced by random fuzzy sets: A general framework for representing uncertain and fuzzy evidence. - Thierry Denoeux (Fuzzy Sets Syst., 2021)

A trivariate Gaussian copula stochastic frontier model with sample selection. - Jianxu Liu; Songsak Sriboonchitta; Aree Wiboonpongse; Thierry Denoeux (Int. J. Approx. Reason., 2021)

An evidential classifier based on Dempster-Shafer theory and deep learning. - Zheng Tong; Philippe Xu; Thierry Denoeux (Neurocomputing, 2021)

Distributed combination of belief functions. - Thierry Denoeux (Inf. Fusion, 2021)

NN-EVCLUS: Neural network-based evidential clustering. - Thierry Denoeux (Inf. Sci., 2021)

Partial classification in the belief function framework. - Liyao Ma; Thierry Denoeux (Knowl. Based Syst., 2021)

Evidence-based recommender system for high-entropy alloys. - Minh-Quyet Ha; Duong-Nguyen Nguyen; Viet Cuong Nguyen; Takahiro Nagata; Toyohiro Chikyow; Hiori Kino; Takashi Miyake; Thierry Denoeux; Van-Nam Huynh; Hieu-Chi Dam (Nat. Comput. Sci., 2021)

A Distributed Rough Evidential K-NN Classifier: Integrating Feature Reduction and Classification. - Zhi-gang Su; Qinghua Hu; Thierry Denoeux (IEEE Trans. Fuzzy Syst., 2021)

Combination of Transferable Classification With Multisource Domain Adaptation Based on Evidential Reasoning. - Zhunga Liu; Linqing Huang; Kuang Zhou; Thierry Denoeux (IEEE Trans. Neural Networks Learn. Syst., 2021)

Trusted Multi-View Deep Learning with Opinion Aggregation. - Wei Liu 027; Xiaodong Yue; Yufei Chen 002; Thierry Denoeux (AAAI, 2022)

A Distributional Approach for Soft Clustering Comparison and Evaluation. - Andrea Campagner; Davide Ciucci; Thierry Denoeux (BELIEF, 2022)

An Evidential Neural Network Model for Regression Based on Random Fuzzy Numbers. - Thierry Denoeux (BELIEF, 2022)

Stable Clustering Ensemble Based on Evidence Theory. - Haijie Fu; Xiaodong Yue; Wei Liu 027; Thierry Denoeux (ICIP, 2022)

Evidence Fusion with Contextual Discounting for Multi-modality Medical Image Segmentation. - Ling Huang 003; Thierry Denoeux; Pierre Vera; Su Ruan (MICCAI (5), 2022)

EGMM: An evidential version of the Gaussian mixture model for clustering. - Lianmeng Jiao; Thierry Denoeux; Zhun-ga Liu; Quan Pan 001 (Appl. Soft Comput., 2022)

Probability and statistics: Foundations and history. Special Issue in honor of Glenn Shafer. - John C. Aldrich; A. Philip Dawid; Thierry Denoeux; Prakash P. Shenoy; Vladimir Vovk (Int. J. Approx. Reason., 2022)

Glenn Shafer - A short biography. - John C. Aldrich; A. Philip Dawid; Thierry Denoeux; Prakash P. Shenoy; Vladimir Vovk (Int. J. Approx. Reason., 2022)

Belief functions and rough sets: Survey and new insights. - Andrea Campagner; Davide Ciucci; Thierry Denoeux (Int. J. Approx. Reason., 2022)

Lymphoma segmentation from 3D PET-CT images using a deep evidential network. - Ling Huang 003; Su Ruan; Pierre Decazes; Thierry Denoeux (Int. J. Approx. Reason., 2022)

Belief Functions on the Real Line Defined by Transformed Gaussian Random Fuzzy Numbers. - Thierry Denoeux (FUZZ, 2023)

Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation. - Ling Huang 003; Su Ruan; Pierre Decazes; Thierry Denoeux (CoRR, 2023)

Semi-supervised multiple evidence fusion for brain tumor segmentation. - Ling Huang 003; Su Ruan; Thierry Denoeux (Neurocomputing, 2023)

Application of belief functions to medical image segmentation: A review. - Ling Huang 003; Su Ruan; Thierry Denoeux (Inf. Fusion, 2023)

Reasoning with fuzzy and uncertain evidence using epistemic random fuzzy sets: General framework and practical models. - Thierry Denoeux (Fuzzy Sets Syst., 2023)

A general framework for evaluating and comparing soft clusterings. - Andrea Campagner; Davide Ciucci; Thierry Denoeux (Inf. Sci., 2023)

Quantifying Prediction Uncertainty in Regression Using Random Fuzzy Sets: The ENNreg Model. - Thierry Denoeux (IEEE Trans. Fuzzy Syst., 2023)

Parametric families of continuous belief functions based on generalized Gaussian random fuzzy numbers. - Thierry Denoeux (Fuzzy Sets Syst., 2023)

A distributional framework for evaluation, comparison and uncertainty quantification in soft clustering. - Andrea Campagner; Davide Ciucci; Thierry Denoeux (Int. J. Approx. Reason., 2023)

Uncertainty Quantification in Regression Neural Networks Using Likelihood-Based Belief Functions. - Thierry Denoeux (BELIEF, 2024)

Combination of Dependent Gaussian Random Fuzzy Numbers. - Thierry Denoeux (BELIEF, 2024)

An Evidential Time-to-Event Prediction Model Based on Gaussian Random Fuzzy Numbers. - Ling Huang 003; Yucheng Xing; Thierry Denoeux; Mengling Feng (BELIEF, 2024)

r-ERBFN: An Extension of the Evidential RBFN Accounting for the Dependence Between Positive and Negative Evidence. - Frédéric Pichon; Serigne Mamadou Diene; Thierry Denoeux; Sébastien Ramel; David Mercier (SUM, 2024)

Evidential time-to-event prediction model with well-calibrated uncertainty estimation. - Ling Huang 003; Yucheng Xing; Swapnil Mishra; Thierry Denoeux; Mengling Feng (CoRR, 2024)

Selecting reliable instances based on evidence theory for transfer learning. - Ying Lv; Bofeng Zhang; Xiaodong Yue; Thierry Denoeux; Shan Yue (Expert Syst. Appl., 2024)

Synergies between machine learning and reasoning - An introduction by the Kay R. Amel group. - Ismaïl Baaj; Zied Bouraoui; Antoine Cornuéjols; Thierry Denoeux; Sébastien Destercke; Didier Dubois; Marie-Jeanne Lesot; João Marques-Silva 001; Jérôme Mengin; Henri Prade; Steven Schockaert; Mathieu Serrurier; et al. (Int. J. Approx. Reason., 2024)

Uncertainty quantification in logistic regression using random fuzzy sets and belief functions. - Thierry Denoeux (Int. J. Approx. Reason., 2024)

Combination of dependent and partially reliable Gaussian random fuzzy numbers. - Thierry Denoeux (Inf. Sci., 2024)

Uncertainty quantification in regression neural networks using evidential likelihood-based inference. - Thierry Denoeux (Int. J. Approx. Reason., 2025)

Evidential time-to-event prediction with calibrated uncertainty quantification. - Ling Huang 003; Yucheng Xing; Swapnil Mishra; Thierry Denoeux; Mengling Feng (Int. J. Approx. Reason., 2025)

Multi-view evidential K-NN classification. - Chaoyu Gong; Zhi-gang Su; Thierry Denoeux (Inf. Fusion, 2025)

Deep evidential fusion with uncertainty quantification and reliability learning for multimodal medical image segmentation. - Ling Huang 003; Su Ruan; Pierre Decazes; Thierry Denoeux (Inf. Fusion, 2025)