4 citations · 6 across the 5 of their papers we have counts for
5 papers
Exploiting Exact Conditionals Improves Conditioning: Provably Fast Mixing Time Bounds By Sampling from the Marginal
Abhijit Chowdhary, Federica Milinanni, Julianne Chung +1
The problem of sampling from a probability distribution arises in many applications such as posterior sampling in hierarchical Bayesian inverse problems and Gaussian processes for…
Boost Like a (Var)Pro: Trust-Region Gradient Boosting via Variable Projection
Abhijit Chowdhary, Elizabeth Newman, Deepanshu Verma
Gradient boosting, a method of building additive ensembles from weak learners, has established itself as a practical and theoretically-motivated approach to approximate functions,…
Robust optimal design of large-scale Bayesian nonlinear inverse problems
Abhijit Chowdhary, Ahmed Attia, Alen Alexanderian
We consider robust optimal experimental design (ROED) for nonlinear Bayesian inverse problems governed by partial differential equations (PDEs). An optimal design is one that maxim…
Sensitivity Analysis of the Information Gain in Infinite-Dimensional Bayesian Linear Inverse Problems
Abhijit Chowdhary, Shanyin Tong, Georg Stadler +1
We study the sensitivity of infinite-dimensional Bayesian linear inverse problems governed by partial differential equations (PDEs) with respect to modeling uncertainties. In parti…
PyOED: An Extensible Suite for Data Assimilation and Model-Constrained Optimal Design of Experiments
Abhijit Chowdhary, Shady E. Ahmed, Ahmed Attia
This paper describes PyOED, a highly extensible scientific package that enables developing and testing model-constrained optimal experimental design (OED) for inverse problems. Spe…