68 citations · 319 across the 71 of their papers we have counts for
4 papers · 1 filter
Optimal Bayesian estimation in random covariate design with a rescaled Gaussian process prior
Debdeep Pati, Anirban Bhattacharya, Guang Cheng
In Bayesian nonparametric models, Gaussian processes provide a popular prior choice for regression function estimation. Existing literature on the theoretical investigation of the…
Adaptive Bayesian Estimation of Conditional Densities
Andriy Norets, Debdeep Pati
We consider a non-parametric Bayesian model for conditional densities. The model is a finite mixture of normal distributions with covariate dependent multinomial logit mixing proba…
Bayesian Semiparametric Multivariate Density Deconvolution
Abhra Sarkar, Debdeep Pati, Bani K. Mallick +1
We consider the problem of multivariate density deconvolution when the interest lies in estimating the distribution of a vector-valued random variable but precise measurements of t…
Dirichlet-Laplace priors for optimal shrinkage
Anirban Bhattacharya, Debdeep Pati, Natesh S. Pillai +1
Penalized regression methods, such as regularization, are routinely used in high-dimensional applications, and there is a rich literature on optimality properties under spars…