Discrete Mumford-Shah on Graph for Mixing Matrix Estimation. - Yacouba Kaloga; Marion Foare; Nelly Pustelnik; Pablo Jensen (IEEE Signal Process. Lett., 2019)

Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening. - Louis Béthune; Yacouba Kaloga; Pierre Borgnat; Aurélien Garivier; Amaury Habrard (Algorithms, 2020)

Multiview Variational Graph Autoencoders for Canonical Correlation Analysis. - Yacouba Kaloga; Pierre Borgnat; Sundeep Prabhakar Chepuri; Patrice Abry; Amaury Habrard (ICASSP, 2021)

Variational graph autoencoders for multiview canonical correlation analysis. - Yacouba Kaloga; Pierre Borgnat; Sundeep Prabhakar Chepuri; Patrice Abry; Amaury Habrard (Signal Process., 2021)

Learning attributed graphs representations. (Apprentissage de représentations de graphes attribués). - Yacouba Kaloga (2021)

A Simple Way to Learn Metrics Between Attributed Graphs. - Yacouba Kaloga; Pierre Borgnat; Amaury Habrard (LoG, 2022)

Graph Neural Networks for Parkinsons Disease Detection. - Shakeel A. Sheikh; Yacouba Kaloga; Md. Sahidullah; Ina Kodrasi (CoRR, 2024)

Multiview Canonical Correlation Analysis for Automatic Pathological Speech Detection. - Yacouba Kaloga; Shakeel A. Sheikh; Ina Kodrasi (ICASSP, 2025)

Graph Neural Networks for Parkinson's Disease Detection. - Shakeel A. Sheikh; Yacouba Kaloga; Md. Sahidullah; Ina Kodrasi (ICASSP, 2025)

A Differentiable Alignment Framework for Sequence-to-Sequence Modeling via Optimal Transport. - Yacouba Kaloga; Shashi Kumar; Petr Motlícek; Ina Kodrasi (CoRR, 2025)