Learning Riemannian metric for disease progression modeling. - Samuel Gruffaz; Pierre-Emmanuel Poulet; Etienne Maheux; Bruno Jedynak; Stanley Durrleman (NeurIPS, 2021)

Stochastic Approximation with Biased MCMC for Expectation Maximization. - Samuel Gruffaz; Kyurae Kim; Alain Durmus; Jacob R. Gardner (AISTATS, 2024)

Shape analysis for time series. - Thibaut Germain; Samuel Gruffaz; Charles Truong; Alain Durmus; Laurent Oudre (NeurIPS, 2024)

Personalized Convolutional Dictionary Learning of Physiological Time Series. - Axel Roques; Samuel Gruffaz; Kyurae Kim; Alain Oliviero Durmus; Laurent Oudre (AISTATS, 2025)

Riemannian Metric Learning: Closer to You than You Imagine. - Samuel Gruffaz; Josua Sassen (CoRR, 2025)