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researcher

Xiaohui Xie

4 papers hereh-index 112 citations4 works total

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

author position
  • sole author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • math.PR1
same name
  • Xiaohui Xie — 38 papers, h 35
  • Xiaohui Xie — 13 papers, h 16
  • Xiaohui Xie — 13 papers, h 44
  • Xiaohui Xie — 12 papers, h 5
  • Xiaohui Xie — 10 papers, h 13
  • Xiaohui Xie — 8 papers, h 3

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
20242026
most citedBiLO: Bilevel Local Operator Learning for PDE Inverse Problems

4 citations · 5 across the 3 of their papers we have counts for

collaborators

4 papers

cs.LG2026

Muon Under Gradient Noise and the Limits of Orthogonalization Near Optima

Xiaohui Xie

Muon replaces the momentum buffer of each weight matrix by its orthogonal polar factor. We ask what this orthogonalization does near an optimum, where minibatch noise dominates the…

math.PR2026

Critical tensor covariance at the Marchenko-Pastur threshold

Xiaohui Xie

For a centered, variance-one random variable X with finite fourth moment, let x be the vector of square-free degree-d monomials in n independent copies of X. At the criti…

cs.LG2025★ 1 cited

Bayesian BiLO: Bilevel Local Operator Learning for Efficient Uncertainty Quantification of Bayesian PDE Inverse Problems with Low-Rank Adaptation

Ray Zirui Zhang, Christopher E. Miles, Xiaohui Xie +1

Uncertainty quantification in PDE inverse problems is essential in many applications. Scientific machine learning and AI enable data-driven learning of model components while prese…

cs.LG2024★ 4 cited

BiLO: Bilevel Local Operator Learning for PDE Inverse Problems

Ray Zirui Zhang, Christopher E. Miles, Xiaohui Xie +1

We propose a new neural network based method for solving inverse problems for partial differential equations (PDEs) by formulating the PDE inverse problem as a bilevel optimization…

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