Simon Bernard

Identifiants chercheurs

IdHAL :

bernasim

ORCID :

0000-0003-0200-4294

IdRef :

143005707

Présentation

I am an associate professor (Maître de Conférence) at the University of Rouen Normandy, and a member of the Machine Learning team of the LITIS lab. (UR 4108). I am also a member of the Data, Learning, Knowledge group in the CNRS Research Federation NormaSTIC (FR 3638).

My research focuses on machine learning, and more specifically on ensemble learning and deep learning methods. In recent years, my work has focused mainly on multi-view/multimodal learning and outlier/anomaly detection. Recently, I've also taken a keen interest in machine learning for physics, with operator learning methods and/or physic-informed learning methods.

I teach computer science and machine learning at the Faculty of Science et Techniques of the University of Rouen Normandy, to bachelor and master students. Today, I mostly teach machine learning and web programming to students of the Data Science master's program.

Publications

Article dans une revue (9)

Multiple Noises in Diffusion Model for Semi-Supervised Multi-Domain Translation Tsiry Mayet,Simon Bernard,Romain Hérault,Clément Chatelain Transactions on Machine Learning Research Journal, 2025 Article dans une revue hal-05273704v1
Pseudo-Labeling With Large Language Models for Multi-Label Emotion Classification of French Tweets Muhammad Usman Malik,Simon Bernard,Alexandre Pauchet,Clément Chatelain,Romain Picot-Clémenteet al. IEEE Access, 2024, 12, pp.15902-15916. ⟨10.1109/ACCESS.2024.3354705⟩ Article dans une revue hal-05273651v1
Random forest kernel for high-dimension low sample size classification Lucca Portes Cavalheiro,Simon Bernard,Jean Paul Barddal,Laurent Heutte Statistics and Computing, 2024, 34 (1), pp.9. ⟨10.1007/s11222-023-10309-0⟩ Article dans une revue hal-04253909v1
Assessment of elastic coefficients of child cortical bone using resonant ultrasound spectroscopy Marie Semaan,Pierric Mora,Simon Bernard,Franck Launay,Cedric Payanet al. Journal of the mechanical behavior of biomedical materials, 2019, 90, pp.40 - 44. ⟨10.1016/j.jmbbm.2018.09.044⟩ Article dans une revue hal-01900136v1
Random forest dissimilarity based multi-view learning for Radiomics application Hongliu Cao,Simon Bernard,Robert Sabourin,Laurent Heutte Pattern Recognition, 2019, 88, pp.185-197. ⟨10.1016/j.patcog.2018.11.011⟩ Article dans une revue hal-02075715v1
The Multiclass ROC Front method for cost-sensitive classification Simon Bernard,Clément Chatelain,Sébastien Adam,Robert Sabourin Pattern Recognition, 2016, ⟨10.1016/j.patcog.2015.10.010⟩ Article dans une revue hal-01338007v1
One class random forests Chesner Désir,Simon Bernard,Caroline Petitjean,Heutte Laurent Pattern Recognition, 2013, 46 (12), pp.3490-3506. ⟨10.1016/j.patcog.2013.05.022⟩ Article dans une revue hal-00862706v1
Mapping Fragmented Agricultural Systems in the Sudano-Sahelian Environments of Africa Using Random Forest and Ensemble Metrics of Coarse Resolution MODIS Imagery Elodie Vintrou,Mamy Soumaré,Simon Bernard,Agnès Bégué,Christian Baronet al. Photogrammetric engineering and remote sensing, 2012, 78 (8), pp.839-848. ⟨10.14358/PERS.78.8.839⟩ Article dans une revue hal-02111056v1
Dynamic Random Forests Simon Bernard,Sébastien Adam,Laurent Heutte Pattern Recognition Letters, 2012, 33 (12), pp.1580-1586. ⟨10.1016/j.patrec.2012.04.003⟩ Article dans une revue hal-00710083v1

Communication dans un congrès (20)

TD-Paint: Faster Diffusion Inpainting Through Time Aware Pixel Conditioning Tsiry Mayet,Pourya Shamsolmoali,Simon Bernard,Eric Granger,Romain Héraultet al. International Conference on Learning Representations (ICLR), 2025, Singapour, France. ⟨10.48550/arXiv.2410.09306⟩ Communication dans un congrès hal-05273670v1
Domain Translation via Latent Space Mapping Tsiry Mayet,Simon Bernard,Clement Chatelain,Romain Hérault 2023 International Joint Conference on Neural Networks (IJCNN), Jun 2023, Gold Coast, Australia. pp.1-10, ⟨10.1109/IJCNN54540.2023.10191215⟩ Communication dans un congrès hal-04461418v1
A Novel Random Forest Dissimilarity Measure for Multi-View Learning Hongliu Cao,Simon Bernard,Robert Sabourin,Laurent Heutte 2020 25th International Conference on Pattern Recognition (ICPR), Jan 2021, Milan, France. pp.1344-1351, ⟨10.1109/ICPR48806.2021.9412961⟩ Communication dans un congrès hal-05311089v1
Dynamic Voting in Multi-view Learning for Radiomics Applications Hongliu Cao,Simon Bernard,Laurent Heutte,Robert Sabourin IAPR Joint International Workshops on Statistical Techniques in Pattern Recognition (SPR 2018) and Structural and Syntactic Pattern Recogntion (SSPR 2018), S+SSPR, Aug 2018, Beijing, China. pp.32-41, ⟨10.1007/978-3-319-97785-0_4⟩ Communication dans un congrès hal-02088181v1
Dissimilarity-based Representation for Radiomics Applications Hongliu Cao,Simon Bernard,Laurent Heutte,Robert Sabourin First International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI'2018), May 2018, Montréal, Canada. pp.53--58 Communication dans un congrès hal-02111139v1
Pondération dynamique en apprentissage multi-vues pour des applications radiomics Hongliu Cao,Simon Bernard,Robert Sabourin,Laurent Heutte Conférence sur l’apprentissage automatique (CAp), Jun 2018, Rouen, France Communication dans un congrès hal-02114995v1
Improve the Performance of Transfer Learning Without Fine-Tuning Using Dissimilarity-Based Multi-view Learning for Breast Cancer Histology Images Hongliu Cao,Simon Bernard,Laurent Heutte,Robert Sabourin International Conference Image Analysis and Recognition (ICIAR), Jun 2018, Póvoa de Varzim, Portugal. pp.779-787, ⟨10.1007/978-3-319-93000-8_88⟩ Communication dans un congrès hal-02088167v1
ROC-based cost-sensitive classification with a reject option Clément Dubos,Simon Bernard,Sébastien Adam,Robert Sabourin 23rd IEEE International Conference on Pattern Recognition (ICPR), Dec 2016, Cancun, Mexico. ⟨10.1109/ICPR.2016.7900146⟩ Communication dans un congrès hal-02088187v1
Apprentissage multiclasse en environnement incertain Simon Bernard,Clément Chatelain,Sébastien Adam,Robert Sabourin Société Francophone de Classification, Sep 2014, Rabat, Maroc Communication dans un congrès hal-02088209v1
A new random forest method for one class classification Chesner Désir,Simon Bernard,Caroline Petitjean,Laurent Heutte Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR), Nov 2012, Hiroshima, Japan. pp.282-290 Communication dans un congrès hal-00794153v1
A random forest based approach for one class classification in medical imaging Chesner Désir,Simon Bernard,Caroline Petitjean,Laurent Heutte 3rd MICCAI International Workshop on Machine Learning in Medical Imaging (MLMI), 2012, Nice, France. pp.250-257 Communication dans un congrès hal-00794160v1
A Study of Strength and Correlation in Random Forests Simon Bernard,Laurent Heutte,Sébastien Adam International Conference on Intelligent Computing, Aug 2010, Changsha, China. pp.186-191, ⟨10.1007/978-3-642-14831-6_25⟩ Communication dans un congrès hal-00598466v1
Influence of Hyperparameters on Random Forest Accuracy Simon Bernard,Laurent Heutte,Sébastien Adam International Workshop on Multiple Classifier Systems (MCS), Jun 2009, Reykjavik, Iceland. pp.171-180, ⟨10.1007/978-3-642-02326-2_18⟩ Communication dans un congrès hal-00436358v1
Towards a better understanding of random forests through the study of strength and correlation Simon Bernard,Laurent Heutte,Sébastien Adam 5th International Conference on Intelligent Computing (ICIC), Sep 2009, Ulsan, South Korea. pp.536-545, ⟨10.1007/978-3-642-04020-7_57⟩ Communication dans un congrès hal-00436361v1
Une étude sur la paramétrisation des Forêts Aléatoires Simon Bernard,Laurent Heutte,Sébastien Adam 11ème Conférence francophone sur l'Apprentissage Artificiel (CAp), May 2009, Hammamet, Tunisie. pp.81-92 Communication dans un congrès hal-00436365v1
On the selection of decision trees in Random Forests Simon Bernard,Laurent Heutte,Sébastien Adam IEEE International Joint Conference on Neural Networks (IJCNN), Jun 2008, Atlanta, United States. pp.302-307, ⟨10.1109/IJCNN.2009.5178693⟩ Communication dans un congrès hal-00436355v1
De la sélection d'arbres de décision dans les forêts aléatoires Laurent Heutte,Simon Bernard,Sébastien Adam,Émilie Oliveira 10ème Colloque International Francophone sur l'Ecrit et le Document (CIFED), Oct 2008, Rouen, France. pp.163-168 Communication dans un congrès hal-00334413v1
Etude de l'influence des paramètres sur les performances des forêts aléatoires Simon Bernard,Laurent Heutte,Sébastien Adam 10ème Colloque International Francophone sur l'Ecrit et le Document (CIFED), Oct 2008, Rouen, France. pp.207-208 Communication dans un congrès hal-00334425v1
Forest-RK: A New Random Forest Induction Method Simon Bernard,Laurent Heutte,Sébastien Adam 4th International Conference on Intelligent Computing (ICIC), Sep 2008, Shanghai, China. pp.430-437, ⟨10.1007/978-3-540-85984-0_52⟩ Communication dans un congrès hal-00436367v1
Using Random Forests for Handwritten Digit Recognition Simon Bernard,Laurent Heutte,Sébastien Adam 9th IAPR/IEEE International Conference on Document Analysis and Recognition (ICDAR), Sep 2007, Curitiba, Brazil. pp.1043-1047, ⟨10.1109/ICDAR.2007.4377074⟩ Communication dans un congrès hal-00436372v1

Chapitre d'ouvrage (1)

Random Forest for Dissimilarity-based Multi-view Learning Simon Bernard,Hongliu Cao,Robert Sabourin,Laurent Heutte Handbook of Pattern Recognition and Computer Vision, 6, World Scientific, pp.119-138, 2020, ⟨10.1142/9789811211072_0007⟩ Chapitre d'ouvrage hal-02892363v1

Thèse (1)

Forêts Aléatoires: De l'Analyse des Mécanismes de Fonctionnement à la Construction Dynamique Simon Bernard Apprentissage [cs.LG]. Université de Rouen, 2009. Français. ⟨NNT : ⟩ Thèse tel-00598441v1