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Yuhong Yang

University of Minnesota

26 papers hereh-index 348k citations130 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author1
  • middle author1
  • last author23

Across the 26 of 26 papers where every author was matched, so the position is known.

fields
  • stat.ME11
  • math.ST8
  • stat.ML3
  • cs.AI1
  • econ.EM1
  • math.CO1
affiliations
  • University of Minnesota
same name
  • Yuhong Yang — 23 papers, h 9
  • Yuhong Yang — 19 papers, h 9
  • Yuhong Yang — 7 papers, h 6
  • Yuhong Yang — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20082026
most citedModel Selection Techniques -- An Overview

395 citations · 692 across the 25 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.AI2026

Self-Representation Alignment in Diffusion Models for Video Background Music Generation

Jincheng Zhang, György Fazekas, Charalampos Saitis

Diffusion models have been widely used for various generative tasks. However, recent studies have demonstrated that the internal representations learned in the diffusion models' de…

stat.ME2026

Transporting Trial Evidence Under Posterior Drift and Possible Hidden Confounding

Xilin Mao, Bosen Cui, Yuhong Yang

Randomized trials provide internally valid treatment-effect evidence, but trial participants may not represent the target population. In contrast, observational studies are often c…

stat.ME2026

Assessing Estimate of CATE from Observational Data via an RCT Study

Bosen Cui, Yuhong Yang

Conditional average treatment effects (CATEs) are increasingly estimated from observational data and used to guide policy and individualized treatment decisions. Before such estima…

stat.ME2026

Combining pre-trained models via localized model averaging

Ziwen Gao, Baihua He, Yuhong Yang

Many pre-trained models (PTMs) are available in modern applications. Because different PTMs are often trained on different datasets, their performances can vary substantially for d…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.