3 papers
stat.ML2026
A Theoretical Comparison of No-U-Turn Sampler Variants: Necessary and Sufficient Convergence Conditions and Mixing Time Analysis under Gaussian Targets
Samuel Gruffaz, Kyurae Kim, Fares Guehtar +2
The No-U-Turn Sampler (NUTS) is the computational workhorse of modern Bayesian software libraries, yet its qualitative and quantitative convergence guarantees were established only…
stat.CO2025
Analysis of kinetic Langevin Monte Carlo under the stochastic exponential Euler discretization from underdamped all the way to overdamped
Kyurae Kim, Samuel Gruffaz, Ji Won Park +1
Simulating the kinetic Langevin dynamics is a popular approach for sampling from distributions, where only their unnormalized densities are available. Various discretizations of th…
stat.ML2025
Personalized Convolutional Dictionary Learning of Physiological Time Series
Axel Roques, Samuel Gruffaz, Kyurae Kim +2
Human physiological signals tend to exhibit both global and local structures: the former are shared across a population, while the latter reflect inter-individual variability. For…