papers

Publications (5)

math.ST2025

Multi-Environment GLAMP: Approximate Message Passing for Transfer Learning with Applications to Lasso-based Estimators

Longlin Wang, Yanke Song, Kuanhao Jiang +1

Approximate Message Passing (AMP) algorithms enable precise characterization of certain classes of random objects in the high-dimensional limit, and have found widespread applicati…

astro-ph.IM2025

A Poisson Process AutoDecoder for X-ray Sources

Yanke Song, Victoria Ashley Villar, Juan Rafael Martinez-Galarza +1

X-ray observing facilities, such as the Chandra X-ray Observatory and the eROSITA, have detected millions of astronomical sources associated with high-energy phenomena. The arrival…

cs.LG2024

Multi-student Diffusion Distillation for Better One-step Generators

Yanke Song, Jonathan Lorraine, Weili Nie +2

Diffusion models achieve high-quality sample generation at the cost of a lengthy multistep inference procedure. To overcome this, diffusion distillation techniques produce student…

math.ST2026

Generalization error of min-norm interpolators in transfer learning

Yanke Song, Kenneth Gu, Sohom Bhattacharya +1

This paper establishes the generalization error of pooled min--norm interpolation in transfer learning, where data from diverse distributions are available. Min-norm interp…

stat.ME2024

HEDE: Heritability estimation in high dimensions by Ensembling Debiased Estimators

Yanke Song, Xihong Lin, Pragya Sur

Estimating heritability remains a significant challenge in statistical genetics. Diverse approaches have emerged over the years that are broadly categorized as either random effect…