Publications | Geraldin Nanfack

Publications

Geraldin Nanfack, Alexander Fulleringer, onathan Marty, Michael Eickenberg, Eugene Belilovsky (2024). Adversarial Attacks on the Interpretation of Neuron Activation Maximization. In AAAI 2024.

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Geraldin Nanfack, Paul Temple, Benoît Frénay (2023). Learning Customised Decision Trees for Domain-knowledge Constraints. Pattern Recognition.

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Hendrik Blockeel, Laurens Devos, Benoît Frénay, Geraldin Nanfack, Siegfried Nijssen (2023). Decision trees: From efficient prediction to responsible AI. Frontiers in Artificial Intelligence, section Machine Learning and Artificial Intelligence.

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Alexandre Englebert, Sédrick Stassin, Geraldin Nanfack, Sidi Ahmed Mahmoudi, Valentin Delchevalerie, Xavier Siebert, Olivier Cornu, Christophe De Vleeschouwer (2023). Explaining through Transformer Input Sampling. In IEEE ICCV Workshops.

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Geraldin Nanfack, Paul Temple, Benoît Frénay (2022). Constraint Enforcement on Decision Trees: a Survey. ACM Computing Surveys.

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Sédrick Stassin, Alexandre Englebert, Gilles Peiffer, Geraldin Nanfack, Julien Albert, Nassim Versbraegen, Miriam Doh, Nicolas Riche, Benoît Frénay, Christophe De Vleeschouwer (2022). An Experimental Investigation into the Evaluation of Explainability Methods. AIMLAI workshop at ECML-PKDD.

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Geraldin Nanfack, Valentin Delchevalerie, Benoît Frénay (2021). Boundary-Based Fairness Constraints in Decision Trees and Random Forests. In ESANN.

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Geraldin Nanfack, Paul Temple, Benoît Frénay (2021). Global Explanations with Decision Rules: a Co-learning Approach. In UAI.

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Adrien Bibal, Minh Viet Vu, Geraldin Nanfack, Benoît Frénay (2020). Explaining t-SNE Embeddings Locally by Adapting LIME. In ESANN.

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Geraldin Nanfack, Azeddine Elhassouny, Rachid Oulad Haj Thami (2018). Squeeze-SegNet: a new fast deep convolutional neural network for semantic segmentation. In ICMV.

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