activity
20112026
most citedPosterior contraction in sparse Bayesian factor models for massive covariance matrices

68 citations · 319 across the 71 of their papers we have counts for

collaborators

79 papers

stat.ME2026

Bayesian Estimation of Continuous Brain Connectivity with Log-Gaussian Cox Processes

Jaehoan Kim, William Consagra, Debdeep Pati +1

Continuous structural connectivity describes the connection between any two points of the cortical surface by an intensity function. Based on the endpoints of tractography streamli…

cs.RO2026

TempoBridge: Language-Guided Tempo Control for Vision-Language-Action Policies

Yeonseo Lee, Hyosup Shin, Guebin Hwang +1

Vision-Language-Action (VLA) models are effective at understanding what task to perform, but provide limited control over how it should be executed, such as moving quickly or slowl…

stat.ME2026

Calibration-Free Robust Bayesian Inference for Discrete Unnormalized Models

Jiongran Wang, Debdeep Pati, Anirban Bhattacharya

Bayesian inference for discrete models with intractable normalizing constants is computationally challenging, particularly when the sample space is large or countably infinite. Alt…

stat.ML2026

Posterior Tempering Explains Variance Inflation in Linear and Generalized Linear Thompson Sampling

Prateek Jaiswal, Debdeep Pati, Anirban Bhattacharya +1

We study a variant of the Thompson Sampling (TS) algorithm, called -TS, for solving stochastic generalized linear bandit problems. Existing analyses of TS require inflating the…

stat.ME2026

Robust Bayesian Inference for Unnormalized Models with Mixed-Domain Data

Jiongran Wang, Debdeep Pati, Anirban Bhattacharya

Many statistical models involve parameter-dependent normalizing constants that are computationally intractable, creating substantial obstacles to standard Bayesian inference. Altho…

stat.ME2026

Robust Simulation Based Inference Through Robust Optimal Transport

Peter Matthew Jacobs, Lekha Patel, Anirban Bhattacharya +1

When a statistical model lacks analytically tractable likelihoods, parametric statistical inference based on data generated from an unknown underlying distributi…