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stat.CO2026
Rapid Mixing of Stereographic MCMC for Heavy-Tailed Sampling
Federica Milinanni, Tyler Farghly, Jun Yang
Sampling from high-dimensional, heavy-tailed distributions is a fundamental challenge in computational statistics, as many standard Markov chain Monte Carlo (MCMC) methods mix poor…
stat.CO2026
Markov Chain Monte Carlo with Diffusion Paths
Han Chen, Sifan Liu, Jun Yang
Sampling from multimodal distributions is a longstanding challenge for classical local Markov chain Monte Carlo (MCMC) methods. A popular remedy is to introduce a sequence of inter…
stat.CO2026
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…