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en:start [2023/01/18 07:17] tdenoeuxen:start [2024/10/09 05:11] (current) tdenoeux
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-{{en:thierry_denoeux.jpg?350}}+{{:en:denoeux_2015.jpg?150|}}
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 Senior member of [[http://www.iufrance.fr|Institut universitaire de France]]\\ Senior member of [[http://www.iufrance.fr|Institut universitaire de France]]\\
-Editor-in-Chief,  [[https://www.journals.elsevier.com/international-journal-of-approximate-reasoning/|International Journal of Approximate Reasoning]]\\ \\ +Editor-in-Chief,  [[http://www.journals.elsevier.com/international-journal-of-approximate-reasoning|International Journal of Approximate Reasoning]]\\ \\
-Director, Laboratory of Excellence [[http://www.utc.fr/labexms2t|MS2T]]\\+
 President, [[https://bfasociety.org|Belief Functions and Applications Society]] President, [[https://bfasociety.org|Belief Functions and Applications Society]]
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 **News:** **News:**
  
-  * Interview on [[https://www.elsevier.com/connect/editors-update/editor-in-a-60-second-spotlight-thierry-denoeux|Elsevier Editor Update]]+  * Interview on [[https://www.elsevier.com/connect/editor-in-a-60-second-spotlight-thierry-denoeux|Elsevier Editor Update]]
   * Interview on [[https://ins2i.cnrs.fr/fr/cnrsinfo/thierry-denoeux-resoudre-des-problemes-dincertitude-au-coeur-de-modeles-informatiques|INS2I web site]]   * Interview on [[https://ins2i.cnrs.fr/fr/cnrsinfo/thierry-denoeux-resoudre-des-problemes-dincertitude-au-coeur-de-modeles-informatiques|INS2I web site]]
-  * Version 2.0.0 of the R package [[https://cran.r-project.org/web/packages/evclass/evclass |evclass]] has been released on CRANThis version contains new functions to express the outputs of trained logistic regressionradial basis function or multi-layer perceptron classifiers as Dempster-Shafer mass functions. (These methods are based on an interpretation of the operations performed in neural networks as the combination of weights of evidence by Dempster's rulesee: {{ :en:publi:nnbelief_kbs_v2_clean.pdf |"T. Denoeux, Logistic Regression, Neural Networks and Dempster-Shafer Theory: a New Perspective. Knowledge-Based Systems 176:54-67, 2019"}}). +  * Article on [[https://www.ins2i.cnrs.fr/fr/cnrsinfo/ia-et-incertitude-une-nouvelle-chaire-iuf-pour-thierry-denoeux|CNRS Sciences Informatiques web site]] 
-  * Version 1.0.0 of the R package [[https://cran.r-project.org/web/packages/evreg/index.html |evreg]] has been released on CRANThis package implements the 'Evidential Neural Network for Regression' (ENNreg) model recently introduced in [[http://example.com|Denoeux (2023a)]] <doi:10.36227/techrxiv.21791831.v1>. In this model, prediction uncertainty is quantified by Gaussian random fuzzy numbers as introduced in Denoeux (2023) <doi:10.1016/j.fss.2022.06.004>. The package contains functions for training the networktuning hyperparameters by cross-validation or the hold-out methodand making predictionsIt also contains utilities for making calculations with Gaussian random fuzzy numbers (such as, e.g., computing the degrees of belief and plausibility of an interval, or combining Gaussian random fuzzy numbers). +  * The [[https://www.bfasociety.org/BFTA2023/|6th School on Belief Functions and their Applications]] took place from Oct27 to Nov 1 at the Japan Advanced Institute of Science and TechnologyIshikawa, Japan. (The slides can be downloaded from the school homepage, and videos of lectures can be viewed on the [[https://www.youtube.com/@bfas_channel|BFAS YouTube channel]]). 
 +  * The [[https://bfasociety.org/Belief2024|8th International Conference on Belief Functions]] was held in BelfastUnited Kingdom, on September 2-42024.
  
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