Robin Louiset

According to our database, Robin Louiset authored at least 11 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Automatic Discovery of Disease Subgroups by Contrasting with Healthy Controls.

Robin Louiset, Edouard Duchesnay, Benoit Dufumier, Antoine Grigis, Pietro Gori

CoRR, May, 2026

Weakly Supervised Segmentation and Classification of Alpha-Synuclein Aggregates in Brightfield Midbrain Images.

Erwan Dereure, Robin Louiset, Laura Parkkinen, David A. Menassa, David Holcman

Proceedings of the 23rd IEEE International Symposium on Biomedical Imaging, 2026

2024

Learning pathological representations in neuroimaging : Predicting psychiatric diagnosis by integrating heterogeneity constraints. (Apprentissage de représentations pathologiques en neuroimagerie : prédiction du diagnostic psychiatrique en intégrant des contraintes d'hétérogénéité).

Robin Louiset

PhD thesis, 2024

Exploring the potential of representation and transfer learning for anatomical neuroimaging: Application to psychiatry.

Benoit Dufumier, Pietro Gori, Sara Petiton, Robin Louiset, Jean-François Mangin, Antoine Grigis, Edouard Duchesnay

NeuroImage, 2024

SepVAE: a contrastive VAE to separate pathological patterns from healthy ones.

Robin Louiset, Edouard Duchesnay, Antoine Grigis, Benoit Dufumier, Pietro Gori

Proceedings of the Medical Imaging with Deep Learning, 3-5 July 2024, Paris, France., 2024

Supervised Diagnosis Prediction from Cortical Sulci: Toward the Discovery of Neurodevelopmental Biomarkers in Mental Disorders.

Pierre Auriau, Antoine Grigis, Benoit Dufumier, Robin Louiset, Joël Chavas, Pietro Gori, Jean-François Mangin, Edouard Duchesnay

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Separating common from salient patterns with Contrastive Representation Learning.

Robin Louiset, Edouard Duchesnay, Antoine Grigis, Pietro Gori

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Double InfoGAN for Contrastive Analysis.

Florence Carton, Robin Louiset, Pietro Gori

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Integrating Prior Knowledge in Contrastive Learning with Kernel.

Benoit Dufumier, Carlo Alberto Barbano, Robin Louiset, Edouard Duchesnay, Pietro Gori

Proceedings of the International Conference on Machine Learning, 2023

2022

Rethinking Positive Sampling for Contrastive Learning with Kernel.

Benoit Dufumier, Carlo Alberto Barbano, Robin Louiset, Edouard Duchesnay, Pietro Gori

CoRR, 2022

2021

UCSL : A Machine Learning Expectation-Maximization Framework for Unsupervised Clustering Driven by Supervised Learning.

Robin Louiset, Pietro Gori, Benoit Dufumier, Josselin Houenou, Antoine Grigis, Edouard Duchesnay

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021