Fédor Moiseev

23 papers receiving 1.1k citations

Fédor Moiseev's Hit Papers

Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned 2019 · 629 citations
6290+2+4Years since publication200400600

Peers

Fédor Moiseev
Comparison fields: 5 of 128
  • Physical Therapy, Sports Therapy and Rehabilitation 76
  • Rehabilitation 95
  • Computer Vision and Pattern Recognition 295
  • Artificial Intelligence 461
  • Human-Computer Interaction 40
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Ewa Piętka Poland
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Abhijit Das India
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István Bíró Hungary
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Citations per year

Countries citing papers authored by Fédor Moiseev

Since Specialization
Citations

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

Fields of papers citing papers by Fédor Moiseev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned
Hit paper breakdown →
2019629
2 2013221
3 201348
4 201441
5 202235
6 200935
7 201029
8 201327
9 201024
10 201316
11 201315
12 200913
13 201012
14 20147
15 20136
16 20155
17 20073
18 20152
19
Biomechanical role of the lacertus fibrosus of the biceps brachialis muscle
20111
20
Automated template based registration of heterogeneous data on human musculoskeletal system
20111

About Fédor Moiseev

Fédor Moiseev is a scholar working on Surgery, Biomedical Engineering, Rehabilitation, Pharmacology and Epidemiology, having authored 27 papers that have together received 1.2k indexed citations. Recurring topics across this work include Shoulder Injury and Treatment (7 papers), Anatomy and Medical Technology (5 papers), Stroke Rehabilitation and Recovery (5 papers), Forensic Anthropology and Bioarchaeology Studies (3 papers), Shoulder and Clavicle Injuries (3 papers), Musculoskeletal pain and rehabilitation (3 papers), Hip disorders and treatments (2 papers) and Human Pose and Action Recognition (2 papers). The work is most often cited by research in Physical Therapy, Sports Therapy and Rehabilitation (76 citations), Rehabilitation (95 citations), Computer Vision and Pattern Recognition (295 citations), Artificial Intelligence (461 citations) and Human-Computer Interaction (40 citations). Fédor Moiseev has collaborated with scholars based in Belgium, Russia and Switzerland. Frequent co-authors include David Talbot, Elena Voita, Ivan Titov, Rico Sennrich, Marcel Rooze, Victor Sholukha, Serge Van Sint Jan, Patrick Salvia, Bruno Bonnechère and Bart Jansen. Their work appears in journals such as Journal of Biomechanics, Gait & Posture, Journal of Manipulative and Physiological Therapeutics, Comptes Rendus Palevol and Clinical Biomechanics.

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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