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Kun Zhang

49 papers hereh-index 4813.2k citations133 works total

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

author position
  • first author6
  • middle author29
  • last author14

Across the 49 of 49 papers where every author was matched, so the position is known.

fields
  • cs.LG33
  • stat.ML6
  • cs.CV3
  • stat.ME3
  • cs.AI2
  • cs.DS1
same name
  • Kun Zhang — 23 papers, h 19
  • Kun Zhang — 20 papers, h 17
  • Kun Zhang — 18 papers, h 17
  • Kun Zhang — 15 papers, h 4
  • Kun Zhang — 14 papers, h 6
  • Kun Zhang — 13 papers, h 13

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
20122022
most citedKernel-based Conditional Independence Test and Application in Causal Discovery

351 citations · 1.2k across the 48 of their papers we have counts for

collaborators
Showing 2018Show all

3 papers · 1 filter

cs.CV2018★ 18 cited

Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping

Huan Fu, Mingming Gong, Chaohui Wang +3

Unsupervised domain mapping aims to learn a function to translate domain X to Y by a function GXY in the absence of paired examples. Finding the optimal GXY without paired data is…

cs.LG2018★ 22 cited

Causal Discovery in the Presence of Missing Data

Ruibo Tu, Kun Zhang, Paul Ackermann +4

Missing data are ubiquitous in many domains including healthcare. When these data entries are not missing completely at random, the (conditional) independence relations in the obse…

cs.DS2018★ 10 cited

Counting and Sampling from Markov Equivalent DAGs Using Clique Trees

AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash +1

A directed acyclic graph (DAG) is the most common graphical model for representing causal relationships among a set of variables. When restricted to using only observational data,…

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