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Yi-Zhuang You

4 papers hereh-index 462 citations11 works total

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

author position
  • middle author2
  • last author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cond-mat.str-el1
same name
  • Yi-Zhuang You — 81 papers, h 40
  • Yi-Zhuang You — 7 papers, h 6
  • Yi-Zhuang You — 7 papers, h 4
  • Yi-Zhuang You — 6 papers, h 3
  • Yi-Zhuang You — 4 papers, h 4
  • Yi-Zhuang You — 2 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
20212023
most citedCategorical Representation Learning: Morphism is All You Need

6 citations · 10 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2023

Data driven modeling for self-similar dynamics

Ruyi Tao, Ningning Tao, Yi-zhuang You +1

Multiscale modeling of complex systems is crucial for understanding their intricacies. Data-driven multiscale modeling has emerged as a promising approach to tackle challenges asso…

cond-mat.str-el2023

Symmetric Mass Generation of Kähler-Dirac Fermions from the Perspective of Symmetry-Protected Topological Phases

Yuxuan Guo, Yi-Zhuang You

The Kähler-Dirac fermion, recognized as an elegant geometric approach, offers an alternative to traditional representations of relativistic fermions. Recent studies have demonstrat…

cs.LG2022★ 4 cited

Categorical Representation Learning and RG flow operators for algorithmic classifiers

Artan Sheshmani, Yizhuang You, Wenbo Fu +1

Following the earlier formalism of the categorical representation learning (arXiv:2103.14770) by the first two authors, we discuss the construction of the "RG-flow based categorifi…

cs.LG2021★ 6 cited

Categorical Representation Learning: Morphism is All You Need

Artan Sheshmani, Yizhuang You

We provide a construction for categorical representation learning and introduce the foundations of "categorifier". The central theme in representation learning is the id…

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