Arthur Flexer

2.2k citations
82 papers · 1.7k · h-index 21

Impact in

Papers in

Arthur Flexer

81 papers receiving 1.5k citations

Peers

Arthur Flexer
Comparison fields: 5 of 126
  • Signal Processing 951
  • Computer Vision and Pattern Recognition 832
  • Cognitive Neuroscience 482
  • Music 50
  • Artificial Intelligence 458
Replace Bob L. T. Sturm with:
Bob L. T. Sturm Denmark
Kazuyoshi Yoshii Japan
Joan Serrà Spain
Michael Mandel United States
Elias Pampalk Austria
Beth Logan United States
Ichiro Fujinaga Canada
Shlomo Dubnov United States
John F. Kolen United States
Shigeki Sagayama Japan
Arthur Flexer relative to Bob L. T. Sturm Denmark Bob L. T. Sturm's profile →
Citations per field
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Bob L. T. Sturm · 1×
Citations per year

Countries citing papers authored by Arthur Flexer

Since Specialization
Citations

This map shows the geographic impact of Arthur Flexer'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 Arthur Flexer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arthur Flexer more than expected).

Fields of papers citing papers by Arthur Flexer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arthur Flexer. 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 Arthur Flexer. The network helps show where Arthur Flexer may publish in the future.

Co-authors

The 25 scholars most cited alongside Arthur Flexer, 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 Arthur Flexer Line = papers co-authored together Arthur Flexer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005170
2 2004121
3 2001101
4 2013101
5 200588
6 200874
7
Local and global scaling reduce hubs in space
201262
8 200755
9 199942
10 201641
11 200241
12
Limitations of Self-organizing Maps for Vector Quantization and Multidimensional Scaling
199641
13 200630
14 201230
15 202029
16 201229
17 200527
18 201526
19 201126
20 201124

About Arthur Flexer

Arthur Flexer is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Artificial Intelligence and Music, having authored 82 papers that have together received 1.7k indexed citations. Recurring topics across this work include Music and Audio Processing (46 papers), Music Technology and Sound Studies (31 papers), Speech and Audio Processing (22 papers), Neural Networks and Applications (13 papers), EEG and Brain-Computer Interfaces (10 papers), Time Series Analysis and Forecasting (10 papers), Video Analysis and Summarization (9 papers) and Neuroscience and Music Perception (9 papers). The work is most often cited by research in Signal Processing (951 citations), Computer Vision and Pattern Recognition (832 citations), Cognitive Neuroscience (482 citations), Music (50 citations) and Artificial Intelligence (458 citations). Arthur Flexer has collaborated with scholars based in Austria, United Kingdom and United States. Frequent co-authors include Gerhard Widmer, Dominik Schnitzer, Georg Dorffner, Elias Pampalk, Markus Schedl, Thomas Grill, Georg B. Gruber, Martin Gasser, Julián Urbano and Herbert Bauer. Their work appears in journals such as Journal of New Music Research, Applied Artificial Intelligence, Journal of Neurosurgical Anesthesiology, Lecture notes in computer science and Bioinformatics.

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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