Pennerath, Frédéric

Associate Professor, Centrale Supelec (Metz)

WG leader

Publications

2025

Research report

  1. 2024 Activity Report — Orpailleur Team (LORIA) : Knowledge Discovery and Knowledge Engineering. Miguel Couceiro, Frédéric Pennerath, Amedeo Napoli, Lydia Boudjeloud-Assala, Brieuc Conan-Guez, Alain Gély.

2024

Conference paper

  1. On the Calibration of Epistemic Uncertainty: Principles, Paradoxes and Conflictual Loss. Mohammed Fellaji, F. Pennerath, Brieuc Conan-Guez, Miguel Couceiro. In proceedings of Machine Learning and Knowledge Discovery in Databases. Research Track European Conference, ECML-PKDD 2024, Vilnius, Lithuania.
  2. Clarity: a Deep Ensemble for Visual Counterfactual Explanations. Claire Theobald, Frédéric Pennerath, Brieuc Conan-Guez, Miguel Couceiro, Amedeo Napoli. In proceedings of The 32th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning., Bruges (Belgium), Belgium.

Research report

  1. 2023 Activity Report – Orpailleur Team (LORIA) : Knowledge Discovery and Knowledge Engineering. Amedeo Napoli, Alexandre Blansché, Lydia Boudjeloud-Assala, Brieuc Conan-Guez, Miguel Couceiro, Alain Gély, Frédéric Pennerath, Yannick Toussaint, Mario Valencia-Pabon.

2021

Conference paper

  1. A Bayesian Convolutional Neural Network for Robust Galaxy Ellipticity Regression. Claire Theobald, Bastien Arcelin, Frédéric Pennerath, Brieuc Conan-Guez, Miguel Couceiro, Amedeo Napoli. In proceedings of ECML PKDD 2021 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Bilbao, Spain.

2020

Conference paper

  1. Discovering Approximate Functional Dependencies using Smoothed Mutual Information. Frédéric Pennerath, Panagiotis Mandros, Jilles Vreeken. In proceedings of KDD 2020 - 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, San Diego / Virtual, United States.
  2. A Bayesian Neural Network based on Dropout Regulation. Claire Theobald, Frédéric Pennerath, Brieuc Conan-Guez, Miguel Couceiro, Amedeo Napoli. In proceedings of Workshop on Uncertainty in Machine Learning (WUML) at ECML-PKDD 2020 Conference, N.A. (online), France.

2018

Conference paper

  1. An Efficient Algorithm for Computing Entropic Measures of Feature Subsets. Frédéric Pennerath. In proceedings of ECML-PKDD 2018 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Dublin, Ireland.

2012

Conference paper

  1. L’extraction de règles de dépendance bien définies entre ensembles de variables multivaluées. Frédéric Pennerath. In proceedings of EGC’2012, Bordeaux, France. Lechevallier, Yves and Melançon, Guy and Pinaud, Bruno (eds). 2012.

2010

Journal

  1. Graph-Mining Algorithm for the Evaluation of Bond Formability. Frédéric Pennerath, Gilles Niel, Philippe Vismara, Philippe Jauffret, Claude Lauren, Amedeo Napoli. Journal of Chemical Information and Modeling, American Chemical Society.

Conference paper

  1. Fast Extraction of Locally Optimal Patterns based on Consistent Pattern Function Variations. Frédéric Pennerath. In proceedings of European Conference on Machine Learning and Knowledge Discovery in Databases 2010, Barcelona, Spain. José L. Balcazar and Francesco Bonchi and Aristides Gionis and Michèle Sebag (eds). 2010.

2009

Conference paper

  1. The Model of Most Informative Patterns and Its Application to Knowledge Extraction from Graph Databases. Frédéric Pennerath, Amedeo Napoli. In proceedings of European Conference, ECML PKDD 2009, Bled, Slovenia. Wray L. Buntine and Marko Grobelnik and Dunja Mladenic and John Shawe-Taylor (eds). 2009.

2008

Journal

  1. La famille des motifs les plus informatifs. Application à l’extraction de graphes en chimie organique. Frédéric Pennerath, Amedeo Napoli. Revue I3 - Information Interaction Intelligence, Cépaduès.

Conference paper

  1. Le problème de l’extraction des graphes informatifs. Application à l’extraction de connaissance à partir de bases de réactions chimiques. Frédéric Pennerath, Amedeo Napoli. In proceedings of 16e congrès francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle - RFIA 2008, Amiens, France.
  2. Mining Intervals of Graphs to Extract Characteristic Reaction Patterns. Frédéric Pennerath, Géraldine Polaillon, Amedeo Napoli. In proceedings of DS 2008, Budapest, Hungary.
  3. A Method for Classifying Vertices of Labeled Graphs Applied to Knowledge Discovery from Molecules. Frédéric Pennerath, Géraldine Polaillon, Amedeo Napoli. In proceedings of ECAI’2008, Patras, Greece.
  4. Prétraitement des bases de données de réactions chimiques pour la fouille de schémas de réactions. Frédéric Pennerath, Géraldine Polaillon, Amedeo Napoli. In proceedings of 8èmes journées Extraction et Gestion des Connaissances, Sophia-Antipolis, France.

2007

Conference paper

  1. Mining Frequent Most Informative Subgraphs. Frédéric Pennerath, Amedeo Napoli. In proceedings of Mining And Learning With Graphs (MLG), Florence, Italy.

2006

Conference paper

  1. La fouille de graphes dans les bases de données réactionnelles au service de la synthèse en chimie organique. Frédéric Pennerath, Amedeo Napoli. In proceedings of 6èmes Journées Francophones “Extraction et gestion des connaissances” - EGC 2006, Lille, France. Gilbert Ritschard, Chabane Djeraba (eds). 2006.

1997

Conference paper

  1. The ATLAS DAQ and event filter prototype ‘-1’ project. L. Mapelli, C. Ottavi, D. Francis, R. Jones, G. Mornacchi, A. Patel, I. Solovev, L. Tremblet, D. Burckhart, M. Cobal, M. Michelotto, M. Niculescu, F. Pennerath, J. Petersen, D. Prigent, J. Rochez, M. Skiadelli, R. Spiwoks, A. Wildish, M. Joos, A. Lacourt, G. Ambrosini, F. Touchard, P. Duval, R. Nacasch, A. Le van Suu, M. Caprini, F. Etienne, Z. Qian, R. Ferrari, A. Mailov, K. Nurdan, G. Unel, G. Polesello, V. Vercesi, F. Scuri, S. Wheeler, S. Kolos. In proceedings of Computing In High-Energy Physics (CHEP 97), Berlin, Germany.
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