activity
20122020
most citedGaussian Process Regression with Location Errors

15 citations · 15 across the 6 of their papers we have counts for

collaborators

15 papers

math.PR2020

Universality and least singular values of random matrix products: a simplified approach

Rohit Chaudhuri, Vishesh Jain, Natesh S. Pillai

In this note, we show how to provide sharp control on the least singular value of a certain translated linearization matrix arising in the study of the local universality of produc…

cs.DS2020

Fast and memory-optimal dimension reduction using Kac's walk

Vishesh Jain, Natesh S. Pillai, Ashwin Sah +2

In this work, we analyze dimension reduction algorithms based on the Kac walk and discrete variants. (1) For points in , we design an optimal Johnson-Lindenstra…

stat.CO2018

Unbiased estimation of log normalizing constants with applications to Bayesian cross-validation

Maxime Rischard, Pierre E. Jacob, Natesh Pillai

Posterior distributions often feature intractable normalizing constants, called marginal likelihoods or evidence, that are useful for model comparison via Bayes factors. This has m…

math.PR2018

Does Hamiltonian Monte Carlo mix faster than a random walk on multimodal densities?

Oren Mangoubi, Natesh S. Pillai, Aaron Smith

Hamiltonian Monte Carlo (HMC) is a very popular and generic collection of Markov chain Monte Carlo (MCMC) algorithms. One explanation for the popularity of HMC algorithms is their…

stat.AP2018

Bias correction in daily maximum and minimum temperature measurements through Gaussian process modeling

Maxime Rischard, Natesh Pillai, Karen A. McKinnon

The Global Historical Climatology Network-Daily database contains, among other variables, daily maximum and minimum temperatures from weather stations around the globe. It is long…

math.PR2017

Mixing Times for a Constrained Ising Process on the Two-Dimensional Torus at Low Density

Natesh S Pillai, Aaron Smith

We study a kinetically constrained Ising process (KCIP) associated with a graph and density parameter ; this process is an interacting particle system with state space $\{ 0…