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Haizhao Yang

8 papers hereh-index 335 citations9 works total

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

author position
  • middle author2
  • last author6

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.AI1
  • cs.CE1
  • cs.SE1
  • math.NA1
  • quant-ph1
same name
  • Haizhao Yang — 78 papers, h 31
  • Haizhao Yang — 15 papers, h 1
  • Haizhao Yang — 11 papers, h 3
  • Haizhao Yang — 6 papers, h 2
  • Haizhao Yang — 5 papers, h 1

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
20232026
most citedNearly Optimal Approximation Rates for Deep Super ReLU Networks on Sobolev Spaces

3 citations · 3 across the 7 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.CE2025

FMint-SDE: A Multimodal Foundation Model for Accelerating Numerical Simulation of SDEs via Error Correction

Jiaxin Yuan, Haizhao Yang, Maria Cameron

Fast and accurate simulation of dynamical systems is a fundamental challenge across scientific and engineering domains. Traditional numerical integrators often face a trade-off bet…

cs.SE2025

Protocode: Prototype-Driven Interpretability for Code Generation in LLMs

Krishna Vamshi Bodla, Haizhao Yang

Since the introduction of Large Language Models (LLMs), they have been widely adopted for various tasks such as text summarization, question answering, speech-to-text translation,…

cs.LG2025

Parsing the Language of Expression: Enhancing Symbolic Regression with Domain-Aware Symbolic Priors

Sikai Huang, Yixin Berry Wen, Tara Adusumilli +2

Symbolic regression is essential for deriving interpretable expressions that elucidate complex phenomena by exposing the underlying mathematical and physical relationships in data.…

cs.LG2025

Curse of Dimensionality in Neural Network Optimization

Sanghoon Na, Haizhao Yang

This paper demonstrates that when a shallow neural network with a Lipschitz continuous activation function is trained using either empirical or population risk to approximate a tar…

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