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researcher

K. Ma

42 papers hereh-index 7217.5k citations604 works total

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

author position
  • middle author6
  • last author35

Across the 41 of 42 papers where every author was matched, so the position is known.

fields
  • cs.HC15
  • cs.LG8
  • cs.GR4
  • cs.SI4
  • cs.CV3
  • cs.DC2
same name
  • K. Ma — 209 papers
  • K. Ma — 30 papers, h 17
  • K. Ma — 17 papers, h 8
  • K. Ma — 9 papers, h 16
  • K. Ma — 8 papers, h 3
  • K. Ma — 8 papers, h 4

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
20082023
most citedSupporting Analysis of Dimensionality Reduction Results with Contrastive Learning

100 citations · 592 across the 42 of their papers we have counts for

collaborators
Showing cs.SIShow all

4 papers · 1 filter

cs.SI2020★ 1 cited

A Visual Analytics Framework for Contrastive Network Analysis

Takanori Fujiwara, Jian Zhao, Francine Chen +1

A common network analysis task is comparison of two networks to identify unique characteristics in one network with respect to the other. For example, when comparing protein intera…

cs.SI2019★ 68 cited

A Deep Generative Model for Graph Layout

Oh-Hyun Kwon, Kwan-Liu Ma

Different layouts can characterize different aspects of the same graph. Finding a "good" layout of a graph is thus an important task for graph visualization. In practice, users oft…

cs.SI2017★ 90 cited

What Would a Graph Look Like in This Layout? A Machine Learning Approach to Large Graph Visualization

Oh-Hyun Kwon, Tarik Crnovrsanin, Kwan-Liu Ma

Using different methods for laying out a graph can lead to very different visual appearances, with which the viewer perceives different information. Selecting a "good" layout metho…

cs.SI2014★ 7 cited

ContactTrees: A Technique for Studying Personal Network Data

Arnaud Sallaberry, Yang-Chih Fu, Hwai-Chung Ho +1

Network visualization allows a quick glance at how nodes (or actors) are connected by edges (or ties). A conventional network diagram of "contact tree" maps out a root and branches…

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