9 citations · 27 across the 30 of their papers we have counts for
7 papers · 1 filter
Inference on Gaussian mixture models with dependent labels
Seunghyun Lee, Rajarshi Mukherjee, Sumit Mukherjee
Gaussian mixture models are widely used to model data generated from multiple latent sources. Despite its popularity, most theoretical research assumes that the labels are either i…
Limits of Absoluteness of Observed Events in Timelike Scenarios: A No-Go Theorem
Sumit Mukherjee, Jonte R. Hance
Wigner's Friend-type paradoxes challenge the assumption that events are absolute -- that when we measure a system, we obtain a single result, which is not relative to anything or a…
CLT in high-dimensional Bayesian linear regression with low SNR
Seunghyun Lee, Nabarun Deb, Sumit Mukherjee
We study central limit theorems for linear statistics in high-dimensional Bayesian linear regression with product priors. Unlike the existing literature where the focus is on poste…
Variational Inference for Latent Variable Models in High Dimensions
Chenyang Zhong, Sumit Mukherjee, Bodhisattva Sen
Variational inference (VI) is a popular method for approximating intractable posterior distributions in Bayesian inference and probabilistic machine learning. In this paper, we int…
Distance-based measures and Epsilon-measures for measurement-based quantum resources
Arindam Mitra, Sumit Mukherjee, Changhyoup Lee
Quantum resource theories provide a structured and elegant framework for quantifying quantum resources. While state-based resource theories have been extensively studied, their mea…
Fluctuations in random field Ising models
Seunghyun Lee, Nabarun Deb, Sumit Mukherjee
This paper establishes a CLT for linear statistics of the form with quantitative Berry-Esseen bounds, where is an observati…