Jason Yust

562 citations
26 papers · 137 · h-index 8

Impact in

  • Music top 1%
    • Musicology and Musical Analysis
    • Music History and Culture
    • Diverse Musicological Studies
    • Diverse Music Education Insights
    • Neuroscience and Music Perception

Papers in

Jason Yust

20 papers receiving 87 citations

Peers

Jason Yust
Comparison fields: 5 of 24
  • Music 91
  • Cognitive Neuroscience 114
  • Signal Processing 53
  • Computer Vision and Pattern Recognition 87
  • Developmental Biology 2
Replace Nicole Biamonte with:
Nicole Biamonte Canada
Christopher Hasty United States
Stefan Kostka United States
Janet Schmalfeldt United States
Trevor de Clercq United States
Ian Quinn United States
Carlos Cancino-Chacón Austria
Charles M. Joseph France
Peter Steinbach Germany
Gaëtan Hadjeres France
Jason Yust relative to Nicole Biamonte Canada Nicole Biamonte's profile →
Citations per field
00.5×2.7×
Nicole Biamonte · 1×
Citations per year

Countries citing papers authored by Jason Yust

Since Specialization
Citations

This map shows the geographic impact of Jason Yust's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jason Yust with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason Yust more than expected).

Fields of papers citing papers by Jason Yust

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jason Yust. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jason Yust. The network helps show where Jason Yust may publish in the future.

Co-authors

The 2 scholars most cited alongside Jason Yust, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jason Yust Line = papers co-authored together Jason Yust links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201618
2 201517
3 201914
4 201710
5 20189
6 20139
7 20158
8 20137
9 20156
10 20146
11 20205
12 20175
13 20185
14 20134
15 20203
16 20223
17 20212
18 20162
19 20201
20 20181

About Jason Yust

Jason Yust is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience, Music, Signal Processing and Automotive Engineering, having authored 26 papers that have together received 137 indexed citations. Recurring topics across this work include Music Technology and Sound Studies (21 papers), Neuroscience and Music Perception (20 papers), Musicology and Musical Analysis (16 papers), Music and Audio Processing (8 papers), Categorization, perception, and language (1 paper), Music History and Culture (1 paper), Spatial Cognition and Navigation (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Music (91 citations), Cognitive Neuroscience (114 citations), Signal Processing (53 citations), Computer Vision and Pattern Recognition (87 citations) and Developmental Biology (2 citations). Jason Yust has collaborated with scholars based in United States, Netherlands and France. Frequent co-authors include John Burgoyne and Emmanuel Amiot. Their work appears in journals such as Journal of Mathematics and Music, Journal of Music Theory, Music Theory Online, Music Theory Spectrum and Music Analysis.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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