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Yuhao Zhou

9 papers hereh-index 73.6k citations11 works total

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

author position
  • first author3
  • middle author5
  • last author1

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • stat.ML5
  • cs.LG2
  • math.OC2
same name
  • Yuhao Zhou — 23 papers, h 10
  • Yuhao Zhou — 22 papers, h 15
  • Yuhao Zhou — 21 papers, h 9
  • Yuhao Zhou — 18 papers, h 6
  • Yuhao Zhou — 7 papers, h 4
  • Yuhao Zhou — 5 papers, h 2

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
20172025
most citedDPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps

290 citations · 476 across the 8 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.LG2022★ 146 cited

DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models

Cheng Lu, Yuhao Zhou, Fan Bao +3

Diffusion probabilistic models (DPMs) have achieved impressive success in high-resolution image synthesis, especially in recent large-scale text-to-image generation applications. A…

cs.LG2022★ 290 cited

DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps

Cheng Lu, Yuhao Zhou, Fan Bao +3

Diffusion probabilistic models (DPMs) are emerging powerful generative models. Despite their high-quality generation performance, DPMs still suffer from their slow sampling as they…

stat.ML2022

Fast Instrument Learning with Faster Rates

Ziyu Wang, Yuhao Zhou, Jun Zhu

We investigate nonlinear instrumental variable (IV) regression given high-dimensional instruments. We propose a simple algorithm which combines kernelized IV methods and an arbitra…

stat.ML2022★ 1 cited

Gradient Estimation with Discrete Stein Operators

Jiaxin Shi, Yuhao Zhou, Jessica Hwang +2

Gradient estimation -- approximating the gradient of an expectation with respect to the parameters of a distribution -- is central to the solution of many machine learning problems…

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