Integrating multi-platform genomic data using hierarchical Bayesian relevance vector machines. - Sanvesh Srivastava; Wenyi Wang 001; Pascal O. Zinn; Rivka R. Colen; Veerabhadran Baladandayuthapani (GENSiPS, 2012)

Integrating multi-platform genomic data using hierarchical Bayesian relevance vector machines. - Sanvesh Srivastava; Wenyi Wang 001; Ganiraju Manyam; Carlos Ordonez 001; Veerabhadran Baladandayuthapani (EURASIP J. Bioinform. Syst. Biol., 2013)

Scalable and Robust Bayesian Inference via the Median Posterior. - Stanislav Minsker; Sanvesh Srivastava; Lizhen Lin; David B. Dunson (ICML, 2014)

WASP: Scalable Bayes via barycenters of subset posteriors. - Sanvesh Srivastava; Volkan Cevher; Quoc Tran-Dinh; David B. Dunson (AISTATS, 2015)

Robust and Scalable Bayes via a Median of Subset Posterior Measures. - Stanislav Minsker; Sanvesh Srivastava; Lizhen Lin; David B. Dunson (J. Mach. Learn. Res., 2017)

Scalable Bayes via Barycenter in Wasserstein Space. - Sanvesh Srivastava; Cheng Li; David B. Dunson (J. Mach. Learn. Res., 2018)

Distributed Bayesian Inference in Linear Mixed-Effects Models. - Sanvesh Srivastava; Yixiang Xu (J. Comput. Graph. Stat., 2021)

Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior. - Rajarshi Guhaniyogi; Cheng Li; Terrance D. Savitsky; Sanvesh Srivastava (J. Mach. Learn. Res., 2022)

Machine Learning and the Future of Bayesian Computation. - Steven Winter; Trevor Campbell; Lizhen Lin; Sanvesh Srivastava; David B. Dunson (CoRR, 2023)

Asynchronous and Distributed Data Augmentation for Massive Data Settings. - Jiayuan Zhou; Kshitij Khare; Sanvesh Srivastava (J. Comput. Graph. Stat., 2023)

SLIM-LLMs: Modeling of Style-Sensory Language RelationshipsThrough Low-Dimensional Representations. - Osama Khalid; Sanvesh Srivastava; Padmini Srinivasan (CoRR, 2025)