11 papers · 1 filter
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 distrib…
A Generalized Tangent Approximation based Variational Inference Framework for Strongly Super-Gaussian Likelihoods
Somjit Roy, Pritam Dey, Debdeep Pati +1
Variational inference, as an alternative to Markov chain Monte Carlo sampling, has played a transformative role in enabling scalable computation for complex Bayesian models. Nevert…
Robust Bayesian Inference on Riemannian Submanifold
Rong Tang, Anirban Bhattacharya, Debdeep Pati +1
Manifold-valued parameters routinely arise in modern statistical applications such as in medical imaging, robotics, and computer vision, to name a few. While traditional Bayesian a…
Stationary Point Constrained Inference via Diffeomorphisms
Michael Price, Debdeep Pati, Ning Ning
Stationary points or derivative zero crossings of a regression function correspond to points where a trend reverses, making their estimation scientifically important. Existing appr…
Global-Local Dirichlet Processes for Identifying Pan-Cancer Subpopulations Using Both Shared and Cancer-Specific Data
Arhit Chakrabarti, Yang Ni, Debdeep Pati +1
We consider the problem of clustering grouped data for which the observations may include group-specific variables in addition to the variables that are shared across groups. This…
An Interpretable Single-Index Mixed-Effects Model for Non-Gaussian National Survey Data
Qingyang Liu, Debdeep Pati, Dipankar Bandyopadhyay
This manuscript presents an innovative statistical model to quantify periodontal disease in the context of complex medical data. A mixed-effects model incorporating skewed random e…