Ariel Ephrat

1.1k citations
10 papers · 617 · 1 hit paper · h-index 7

Impact in

Papers in

Ariel Ephrat

10 papers receiving 605 citations

Ariel Ephrat's Hit Papers

Looking to listen at the cocktail party 2018 · 388 citations
3880+2+5Years since publication100200300

Peers

Ariel Ephrat
Comparison fields: 5 of 66
  • Signal Processing 437
  • Computer Vision and Pattern Recognition 210
  • Artificial Intelligence 211
  • Cognitive Neuroscience 92
  • Computational Mechanics 70
Replace Jianwei Yu with:
Jianwei Yu China
Nicholas J. Bryan United States
Flávio Ribeiro Brazil
Şefik Emre Eskimez United States
Slim Essid France
Ruohan Gao United States
Gilbert Maître Switzerland
Shinji Takaki Japan
Rudrabha Mukhopadhyay India
Shinnosuke Takamichi Japan
Ariel Ephrat relative to Jianwei Yu China Jianwei Yu's profile →
Citations per field
00.5×
Jianwei Yu · 1×
Citations per year

Countries citing papers authored by Ariel Ephrat

Since Specialization
Citations

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

Fields of papers citing papers by Ariel Ephrat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Ariel Ephrat, 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 Ariel Ephrat Line = papers co-authored together Ariel Ephrat links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
Looking to listen at the cocktail party
Hit paper breakdown →
2018388
2 201774
3 202452
4 201837
5 202323
6 201921
7
Seeing Through Noise: Speaker Separation and Enhancement using Visually-derived Speech.
201711
8 20186
9 20243
10 20252

About Ariel Ephrat

Ariel Ephrat is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Oceanography and Cognitive Neuroscience, having authored 10 papers that have together received 617 indexed citations. Recurring topics across this work include Music and Audio Processing (5 papers), Speech and Audio Processing (5 papers), Generative Adversarial Networks and Image Synthesis (3 papers), Video Analysis and Summarization (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Advanced X-ray and CT Imaging (1 paper), Advanced Vision and Imaging (1 paper) and Advanced Data Compression Techniques (1 paper). The work is most often cited by research in Signal Processing (437 citations), Computer Vision and Pattern Recognition (210 citations), Artificial Intelligence (211 citations), Cognitive Neuroscience (92 citations) and Computational Mechanics (70 citations). Ariel Ephrat has collaborated with scholars based in Israel, United States and United Kingdom. Frequent co-authors include Inbar Mosseri, Tali Dekel, Michael Rubinstein, Oran Lang, William T. Freeman, Kevin Wilson, Avinatan Hassidim, Leo Joskowicz, Shiran Zada and Omer Tov. Their work appears in journals such as ACM Transactions on Graphics, Medical & Biological Engineering & Computing and arXiv (Cornell University).

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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