| 2026 | ICPR | Robust Explanations Through Uncertainty Decomposition: A Path to Trustworthier AI. | Chenrui Zhu, Louenas Bounia, Vu-Linh Nguyen, Sbastien Destercke, Arthur Hoarau |
| 2026 | KR | Belief Function Propagation in Quantitative Bipolar Argumentation Frameworks. | Jordan Thieyre, Aurlie Beynier, Sbastien Destercke, Nicolas Maudet, Srdjan Vesic |
| 2025 | ECAI | Uncertainty in Quantitative Bipolar Argumentation Frameworks. | Jordan Thieyre, Caren Al Anaissy, Aurlie Beynier, Sbastien Destercke, Nicolas Maudet, Srdjan Vesic |
| 2025 | ECSQARU | Possibilistic Logic and Inference for Linear Systems. | Armand Gaudillier, Khaled Belahcne, Wassila Ouerdane, Sbastien Destercke |
| 2025 | ECSQARU | Discrete Minimax Probabilistic Classifier Chains for Multi-label Classification Under Label Imbalance. | Salvador Madrigal, Cyprien Gilet, Vu-Linh Nguyen, Sbastien Destercke |
| 2025 | ECSQARU | Uncertainty in Quantitative Bipolar Argumentation Frameworks. | Jordan Thieyre, Caren Al Anaissy, Aurlie Beynier, Sbastien Destercke, Nicolas Maudet, Srdjan Vesic |
| 2025 | ECSQARU | Robust Explanations: The Case of Prime Implicants. | Chenrui Zhu, Vu-Linh Nguyen, Marie-Hlne Masson, Sbastien Destercke |
| 2025 | EUSFLAT | Robust Decisions: Bridging the Quantitative-Qualitative Gap. | Sbastien Destercke, Agns Rico |
| 2025 | UAI | Guaranteed Prediction Sets for Functional Surrogate Models. | Ander Gray, Vignesh Gopakumar, Sylvain Rousseau, Sbastien Destercke |
| 2024 | ECAI | Principled Explanations for Robust Redistributive Decisions. | Hnok Willot, Khaled Belahcne, Sbastien Destercke |
| 2024 | IPMU | Geospatial Uncertainties: A Focus on Intervals and Spatial Models Based on Inverse Distance Weighting. | Priscillia Labourg, Sbastien Destercke, Romain Guillaume, Jrmy Rohmer, Benjamin Quost, Stphane Belbze |
| 2024 | IPMU | Suppressing Impulse Noise via Cloud Filtering. | Olivier Strauss, Frdric Comby, Sbastien Destercke |
| 2024 | IGARSS | Robust Confidence Intervals for Digital Surface Models Using Satellite Photogrammetry. | Roman Malinowski, Emmanuelle Sarrazin, Emmanuel Dubois, Loc Dumas, Sbastien Destercke |
| 2023 | ECSQARU | Handling Inconsistency in (Numerical) Preferences Using Possibility Theory. | Loc Adam, Sbastien Destercke |
| 2023 | ECSQARU | On the Enumeration of Non-dominated Spanning Trees with Imprecise Weights. | Tom Davot, Sbastien Destercke, David Savourey |
| 2023 | ECSQARU | Learning Sets of Probabilities Through Ensemble Methods. | Vu-Linh Nguyen, Haifei Zhang, Sbastien Destercke |
| 2022 | IPMU | A Robust Bayesian Estimation Approach for the Imprecise Plackett-Luce Model. | Tathagata Basu, Sbastien Destercke, Benjamin Quost |
| 2022 | IPMU | Necessary and Possibly Optimal Items in Selecting Problems. | Sbastien Destercke, Romain Guillaume |
| 2022 | UAI | Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison. | Eyke Hllermeier, Sbastien Destercke, Mohammad Hossein Shaker |
| 2021 | ECSQARU | Multi-label Chaining with Imprecise Probabilities. | Yonatan Carlos Carranza Alarcn, Sbastien Destercke |
| 2021 | UAI | Possibilistic preference elicitation by minimax regret. | Loc Adam, Sbastien Destercke |
| 2020 | IPMU | Cautious Label-Wise Ranking with Constraint Satisfaction. | Yonatan Carlos Carranza Alarcn, Soundouss Messoudi, Sbastien Destercke |
| 2020 | IPMU | Approximating General Kernels by Extended Fuzzy Measures: Application to Filtering. | Sbastien Destercke, Agns Rico, Olivier Strauss |
| 2020 | IPMU | Handling Mixture Optimisation Problem Using Cautious Predictions and Belief Functions. | Lucie Jacquin, Abdelhak Imoussaten, Sbastien Destercke |
| 2020 | IPMU | Deep Conformal Prediction for Robust Models. | Soundouss Messoudi, Sylvain Rousseau, Sbastien Destercke |
| 2020 | IPMU | Dealing with Inconsistent Measurements in Inverse Problems: An Approach Based on Sets and Intervals. | Krushna Shinde, Pierre Feissel, Sbastien Destercke |
| 2019 | DIS | Epistemic Uncertainty Sampling. | Vu-Linh Nguyen, Sbastien Destercke, Eyke Hllermeier |
| 2019 | IJCAI | How to Handle Missing Values in Multi-Criteria Decision Aiding?. | Christophe Labreuche, Sbastien Destercke |
| 2018 | IJCAI | Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty. | Vu-Linh Nguyen, Sbastien Destercke, Marie-Hlne Masson, Eyke Hllermeier |
| 2017 | AAAI | Querying Partially Labelled Data to Improve a K-nn Classifier. | Vu-Linh Nguyen, Sbastien Destercke, Marie-Hlne Masson |
| 2017 | ECSQARU | A Generic Framework to Include Belief Functions in Preference Handling for Multi-criteria Decision. | Sbastien Destercke |
| 2016 | IPMU | Comparing System Reliabilities with Ill-Known Probabilities. | Lanting Yu, Sbastien Destercke, Mohamed Sallak, Walter Schn |
| 2015 | ECSQARU | Elicitation of a Utility from Uncertainty Equivalent Without Standard Gambles. | Christophe Labreuche, Sbastien Destercke, Brice Mayag |
| 2015 | EUSFLAT | Evidential likelihood flatness as a way tomeasure data quality: the multinomial case. | Liyao Ma, Sbastien Destercke, Yong Wang |
| 2015 | UAI | Optimal expert elicitation to reduce interval uncertainty. | Nadia Ben Abdallah, Sbastien Destercke |
| 2014 | ECAI | Nested Dichotomies with probability sets for multi-class classification. | Gen Yang, Sbastien Destercke, Marie-Hlne Masson |
| 2014 | IPMU | Multilabel Prediction with Probability Sets: The Hamming Loss Case. | Sbastien Destercke |
| 2014 | IPMU | Kolmogorov-Smirnov Test for Interval Data. | Sbastien Destercke, Olivier Strauss |
| 2014 | IPMU | Application of E 2 M Decision Trees to Rubber Quality Prediction. | Nicolas Sutton-Charani, Sbastien Destercke, Thierry Denoeux |
| 2014 | IPMU | A Note on Learning Dependence under Severe Uncertainty. | Matthias C. M. Troffaes, Frank P. A. Coolen, Sbastien Destercke |
| 2013 | ECSQARU | Extreme Points of the Credal Sets Generated by Elementary Comparative Probabilities. | Enrique Miranda, Sbastien Destercke |
| 2013 | ECSQARU | Selecting Source Behavior in Information Fusion on the Basis of Consistency and Specificity. | Frdric Pichon, Sbastien Destercke, Thomas Burger |
| 2013 | ICMLA | Learning Decision Trees from Uncertain Data with an Evidential EM Approach. | Nicolas Sutton-Charani, Sbastien Destercke, Thierry Denoeux |
| 2011 | ECSQARU | Independence and 2-Monotonicity: Nice to Have, Hard to Keep. | Sbastien Destercke |
| 2011 | EUSFLAT | F-boxes for filtering. | Olivier Strauss, Sbastien Destercke |
| 2011 | EUSFLAT | On the connection between probability boxes and possibility measures. | Matthias C. M. Troffaes, Enrique Miranda, Sbastien Destercke |
| 2011 | FQAS | Data Reliability Assessment in a Data Warehouse Opened on the Web. | Sbastien Destercke, Patrice Buche, Brigitte Charnomordic |
| 2010 | IPMU | A K-Nearest Neighbours Method Based on Lower Previsions. | Sbastien Destercke |
| 2010 | IPMU | A New Contextual Discounting Rule for Lower Probabilities. | Sbastien Destercke |
| 2010 | IPMU | Using Cloudy Kernels for Imprecise Linear Filtering. | Sbastien Destercke, Olivier Strauss |
| 2010 | KSEM | Making Ontology-Based Knowledge and Decision Trees Interact: An Approach to Enrich Knowledge and Increase Expert Confidence in Data-Driven Models. | Iyan Johnson, Jol Abcassis, Brigitte Charnomordic, Sbastien Destercke, Rallou Thomopoulos |
| 2009 | ECSQARU | Can the Minimum Rule of Possibility Theory Be Extended to Belief Functions?. | Sbastien Destercke, Didier Dubois |
| 2007 | ECSQARU | Cautious Conjunctive Merging of Belief Functions. | Sbastien Destercke, Didier Dubois, Eric Chojnacki |
| 2007 | EUSFLAT | Transforming Probability Intervals into Other Uncertainty Models. | Sbastien Destercke, Didier Dubois, Eric Chojnacki |