| Learning disentangled representations via mutual information estimation EH Sanchez, M Serrurier, M Ortner Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 90 | 2020 |
| Agents that argue and explain classifications L Amgoud, M Serrurier Autonomous Agents and Multi-Agent Systems 16, 187-209, 2008 | 68 | 2008 |
| Statistical prediction of aircraft trajectory: regression methods vs point-mass model MG Hamed, D Gianazza, M Serrurier, N Durand ATM 2013, 10th USA/Europe Air Traffic Management Research and Development …, 2013 | 55 | 2013 |
| Achieving robustness in classification using optimal transport with hinge regularization M Serrurier, F Mamalet, A González-Sanz, T Boissin, JM Loubes, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 52 | 2021 |
| Naive possibilistic classifiers for imprecise or uncertain numerical data M Bounhas, MG Hamed, H Prade, M Serrurier, K Mellouli Fuzzy Sets and Systems 239, 137-156, 2014 | 50 | 2014 |
| Possibilistic classifiers for numerical data M Bounhas, K Mellouli, H Prade, M Serrurier Soft Computing 17, 733-751, 2013 | 45 | 2013 |
| Learning fuzzy rules with their implication operators M Serrurier, D Dubois, H Prade, T Sudkamp Data & Knowledge Engineering 60 (1), 71-89, 2007 | 41 | 2007 |
| Pay attention to your loss: understanding misconceptions about lipschitz neural networks L Béthune, A González-Sanz, F Mamalet, M Serrurier Advances in Neural Information Processing Systems, 2022, 2022 | 38* | 2022 |
| Visualization of frequent itemsets with nested circular layout and bundling algorithm G Bothorel, M Serrurier, C Hurter Advances in Visual Computing: 9th International Symposium, ISVC 2013 …, 2013 | 38 | 2013 |
| An automatic generation of schematic maps to display flight routes for air traffic controllers: structure and color optimization C Hurter, M Serrurier, R Alonso, G Tabart, JL Vinot Proceedings of the international conference on advanced visual interfaces …, 2010 | 36 | 2010 |
| Elicitating Sugeno integrals: Methodology and a case study H Prade, A Rico, M Serrurier, E Raufaste Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 10th …, 2009 | 36 | 2009 |
| Introducing possibilistic logic in ILP for dealing with exceptions M Serrurier, H Prade Artificial Intelligence 171 (16-17), 939-950, 2007 | 34 | 2007 |
| Improving inductive logic programming by using simulated annealing M Serrurier, H Prade Information sciences 178 (6), 1423-1441, 2008 | 32 | 2008 |
| An informational distance for estimating the faithfulness of a possibility distribution, viewed as a family of probability distributions, with respect to data M Serrurier, H Prade International journal of approximate reasoning 54 (7), 919-933, 2013 | 30 | 2013 |
| ARPEGE cloud cover forecast postprocessing with convolutional neural network F Dupuy, O Mestre, M Serrurier, VK Burdá, M Zamo, ... Weather and Forecasting 36 (2), 567-586, 2021 | 29 | 2021 |
| Arguing and explaining classifications L Amgoud, M Serrurier Argumentation in Multi-Agent Systems: 4th International Workshop, ArgMAS …, 2008 | 28 | 2008 |
| Analogical classifiers: A theoretical perspective N Hug, H Prade, G Richard, M Serrurier ECAI 2016, 689-697, 2016 | 27 | 2016 |
| Statistical prediction of aircraft trajectory: regression methods vs point-mass model M Ghasemi Hamed, D Gianazza, M Serrurier, N Durand ATM Seminar, 2013 | 27 | 2013 |
| Bipolar version space learning H Prade, M Serrurier International Journal of Intelligent Systems 23 (10), 1135-1152, 2008 | 26 | 2008 |
| Dyslexia and Dysgraphia prediction: A new machine learning approach G Richard, M Serrurier arXiv preprint arXiv:2005.06401, 2020 | 25 | 2020 |
