54 citations · 170 across the 45 of their papers we have counts for
24 papers · 1 filter
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…
Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests
Somjit Roy, Pritam Dey, Bani K. Mallick +1
Symbolic regression has emerged as a powerful tool for artificial intelligence-driven scientific discovery by learning interpretable analytical expressions that reveal governing re…
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…
Orthogonal calibration via posterior projections with applications to the Schwarzschild model
Antik Chakraborty, Jonelle B. Walsh, Louis Strigari +2
The orbital superposition method originally developed by Schwarzschild (1979) is used to study the dynamics of growth of a black hole and its host galaxy, and has uncovered new rel…
Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data
Yabo Niu, Yang Ni, Debdeep Pati +1
In a traditional Gaussian graphical model, data homogeneity is routinely assumed with no extra variables affecting the conditional independence. In modern genomic datasets, there i…
An Approximate Bayesian Approach to Covariate-dependent Graphical Modeling
Sutanoy Dasgupta, Peng Zhao, Jacob Helwig +3
Gaussian graphical models typically assume a homogeneous structure across all subjects, which is often restrictive in applications. In this article, we propose a weighted pseudo-li…