68 citations · 353 across the 57 of their papers we have counts for
66 papers
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…
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…
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…
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…
Frequentist Regret Analysis of Gaussian Process Thompson Sampling via Fractional Posteriors
Somjit Roy, Prateek Jaiswal, Anirban Bhattacharya +2
We study Gaussian Process Thompson Sampling (GP-TS) for sequential decision-making over compact, continuous action spaces and provide a frequentist regret analysis based on fractio…
On Quantification of Borrowing of Information in Hierarchical Bayesian Models
Prasenjit Ghosh, Anirban Bhattacharya, Debdeep Pati
In this work, we offer a thorough analytical investigation into the role of shared hyperparameters in a hierarchical Bayesian model, examining their impact on information borrowing…