Machine Learning to Predict Toxicity of Compounds. - Ingrid Grenet; Yonghua Yin; Jean-Paul Comet; Erol Gelenbe (ICANN (1), 2018)

G-Networks to Predict the Outcome of Sensing of Toxicity. - Ingrid Grenet; Yonghua Yin; Jean-Paul Comet (Sensors, 2018)

Stacked Generalization with Applicability Domain Outperforms Simple QSAR on in Vitro Toxicological Data. - Ingrid Grenet; Kevin Merlo; Jean-Paul Comet; Romain Tertiaux; David Rouquié; Frédéric Dayan (J. Chem. Inf. Model., 2019)

Evaluation of the use of public toxicological data for chemical hazard prediction through computational methods. (De l'utilisation des données publiques pour la prédiction de la toxicité des produits chimiques). - Ingrid Grenet (2019)

PaZoe: classifying time series with few labels. - Mikhail Kamalov; Aurélie Boisbunon; Carlo Fanara; Ingrid Grenet; Jonathan Daeden (EUSIPCO, 2021)

Zoetrope genetic programming for regression. - Aurélie Boisbunon; Carlo Fanara; Ingrid Grenet; Jonathan Daeden; Alexis Vighi; Marc Schoenauer (GECCO, 2021)

ZGP appliqué à la segmentation des images hyperspectrales. - Ingrid Grenet; Yves Bobichon; Adrien Girard (APIA, 2023)

SGraphZoe: Explainable self-supervised framework for signal-based anomaly detection. - Mikhail Kamalov; Luca Uggeri; Ingrid Grenet; Jonathan Daeden (DSP, 2023)

Détection d'anomalies à bord de satellites pour la protection de l'environnement marin. - Thomas Goudemant; Clotilde Szywala; Benjamin Francesconi; Michelle Aubrun; Erwann Kervennic; Ingrid Grenet; Yves Bobichon; Marjorie Bellizzi; Adrien Girard (APIA, 2024)

Onboard Anomaly Detection for Marine Environmental Protection. - Thomas Goudemant; Benjamin Francesconi; Michelle Aubrun; Erwann Kervennic; Ingrid Grenet; Yves Bobichon; Marjorie Bellizzi (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)