Author

A. Bhattacharya

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Preprint Oct 2026

Calibration-Free Robust Bayesian Inference for Discrete Unnormalized Models

Bayesian inference for discrete models with intractable normalizing constants is computationally challenging, particularly when the sample space is large or countably infinite. Although some likelihood-based Bayesian methods can circumvent the intractable normalizing constant, their uncertainty quantification may be po...

Jiong-Ran Wang, D. Pati, A. Bhattacharya · 0 citations

Preprint Sep 2026

Robust Bayesian Inference for Unnormalized Models with Mixed-Domain Data

Results show that SME-BETEL credible sets are asymptotically calibrated to the sampling variability of the score matching estimator, yielding valid frequentist coverage under model misspecification and prove a Bernstein-von Mises theorem for the SME-BETEL posterior.

Jiong-Ran Wang, D. Pati, A. Bhattacharya · 1 citation

#machine learning Preprint Sep 2026

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

This work introduces a variant of the Thompson Sampling algorithm that uses a fractional or $\alpha$-posterior instead of the standard posterior, and identifies general regularity conditions on the prior and reward distributions that enable a regret analysis of $\alpha$-TS without assuming any tractable approximation o...

Prateek Jaiswal, D. Pati, A. Bhattacharya et al. · 0 citations