1 code implementation • 2 May 2024 • Alessio Xompero, Myriam Bontonou, Jean-Michel Arbona, Emmanouil Benetos, Andrea Cavallaro
To explain the decision of these models, we use feature-attribution to identify and quantify which objects (and which of their features) are more relevant to privacy classification with respect to a reference input (i. e., no objects localised in an image) predicted as public.
1 code implementation • 1 Feb 2024 • Myriam Bontonou, Anaïs Haget, Maria Boulougouri, Benjamin Audit, Pierre Borgnat, Jean-Michel Arbona
A collection of machine learning models including logistic regression, multilayer perceptron, and graph neural network are trained to classify samples according to their cancer type.
1 code implementation • 19 Mar 2023 • Myriam Bontonou, Anaïs Haget, Maria Boulougouri, Jean-Michel Arbona, Benjamin Audit, Pierre Borgnat
The scientific questions are formulated as classical learning problems on tabular data or on graphs, e. g. phenotype prediction from gene expression data.