From the 1 of 5 linked papers with an AI index.
5 papers
Markov Chain Monte Carlo with Diffusion Paths
Han Chen, Sifan Liu, Jun Yang
The paper proposes a new MCMC method that interpolates between a target distribution and a Gaussian using diffusion paths, preserving mode weights and improving mixing, and introdu…
Stereographic Multiple-Try Metropolis
Zhihao Wang, Jun Yang
Multiple-proposal MCMC algorithms have recently gained attention for their potential to improve performance, especially through parallel implementation on modern hardware. We intro…
Sub-Cauchy Sampling: Escaping the Dark Side of the Moon
Sebastiano Grazzi, Sifan Liu, Gareth O. Roberts +1
We introduce a Markov chain Monte Carlo algorithm based on Sub-Cauchy Projection, a geometric transformation that generalizes stereographic projection by mapping Euclidean space in…
Finding Non-Redundant Simpson's Paradox from Multidimensional Data
Yi Yang, Jian Pei, Jun Yang +1
Simpson's paradox, a long-standing statistical phenomenon, describes the reversal of an observed association when data are disaggregated into sub-populations. It has critical impli…
Wasserstein and Convex Gaussian Approximations for Non-stationary Time Series of Diverging Dimensionality
Miaoshiqi Liu, Jun Yang, Zhou Zhou
In high-dimensional time series analysis, Gaussian approximation (GA) schemes under various distance measures or on various collections of subsets of the Euclidean space play a fun…