3 papers
stat.ME2026
Bayesian Graphical Models under Positivity Constraints: A Scalable generalized likelihood Approach
Swarnali Raha, Partha Sarkar, Sirani Perera +1
We develop a computationally scalable Bayesian framework for precision matrix estimation in Gaussian graphical models under total positivity constraints. To overcome the high compu…
math.ST2026
Moment bounds for condition numbers and singular values of high-dimensional Gaussian random matrices: Applications and limitations
Partha Sarkar, Kshitij Khare, Sanvesh Srivastava
Spectral properties of Gram matrices are central to high dimensional asymptotic analyses of statistical estimators in regression and covariance estimation. These properties, in tur…
stat.ME2026
CoMET: A Compressed Bayesian Mixed-Effects Model for High-Dimensional Tensors
Sreya Sarkar, Kshitij Khare, Sanvesh Srivastava
Mixed-effects models are fundamental tools for analyzing clustered and repeated-measures data, but existing high-dimensional methods largely focus on penalized estimation with vect…