6 citations · 10 across the 12 of their papers we have counts for
13 papers
Asymptotic analysis of rare events in high dimensions
Anya Katsevich, Alexander Katsevich
Understanding rare events is critical across domains ranging from signal processing to reliability and structural safety, extreme-weather forecasting, and insurance. The analysis o…
A unified theory of the high-dimensional Laplace approximation with application to Bayesian inverse problems
Anya Katsevich, Vladimir Spokoiny
The Laplace approximation (LA) to posteriors is a ubiquitous tool to simplify Bayesian computation, particularly in the high-dimensional settings arising in Bayesian inverse proble…
The Laplace asymptotic expansion in high dimensions
Anya Katsevich
We prove that the classical Laplace asymptotic expansion (AE) of , extends to the high-dimensional regime in which may grow large w…
Improved dimension dependence in the Bernstein von Mises Theorem via a new Laplace approximation bound
Anya Katsevich
The Bernstein-von Mises theorem (BvM) gives conditions under which the posterior distribution of a parameter based on independent samples is asympto…
The Laplace approximation accuracy in high dimensions: a refined analysis and new skew adjustment
Anya Katsevich
In Bayesian inference, making deductions about a parameter of interest requires one to sample from or compute an integral against a posterior distribution. A popular method to make…
Tight Bounds on the Laplace Approximation Accuracy in High Dimensions
Anya Katsevich
In Bayesian inference, a widespread technique to compute integrals against a high-dimensional posterior is to use a Gaussian proxy to the posterior known as the Laplace approximati…