Arber Zela

34 total papers · 863 total citations
5 papers, 77 citations indexed

About

Arber Zela is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Materials Chemistry. According to data from OpenAlex, Arber Zela has authored 5 papers receiving a total of 77 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 1 paper in Materials Chemistry. Recurrent topics in Arber Zela's work include Domain Adaptation and Few-Shot Learning (3 papers), Advanced Neural Network Applications (3 papers) and Adversarial Robustness in Machine Learning (2 papers). Arber Zela is often cited by papers focused on Domain Adaptation and Few-Shot Learning (3 papers), Advanced Neural Network Applications (3 papers) and Adversarial Robustness in Machine Learning (2 papers). Arber Zela collaborates with scholars based in Germany, Switzerland and United States. Arber Zela's co-authors include Frank Hutter, Thomas Brox, Thomas Elsken, Tonmoy Saikia, Yassine Marrakchi, Jan Hendrik Metzen, Rohit Mohan, Benedikt Staffler, Josif Grabocka and Abhinav Valada and has published in prestigious journals such as International Journal of Computer Vision, Journal of Clinical Medicine and arXiv (Cornell University).

In The Last Decade

Arber Zela

4 papers receiving 72 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Arber Zela	60	55	6	6	3	5	77
Ju Xu	85 1.4×	57 1.0×	4 0.7×	3 0.5×	2 0.7×	6	106
Satish Nadathur	34 0.6×	34 0.6×	13 2.2×	3 0.5×	3 1.0×	3	69
Grace Chu	52 0.9×	54 1.0×	10 1.7×	3 0.5×		3	71
Utku Evci	38 0.6×	29 0.5×	4 0.7×	3 0.5×		6	44
Zhenzhi Wang	63 1.1×	126 2.3×	8 1.3×	10 1.7×	1 0.3×	8	228
Greg Diamos	50 0.8×	42 0.8×	24 4.0×	7 1.2×	1 0.3×	5	101
Rao Muhammad Umer	24 0.4×	41 0.7×	4 0.7×		3 1.0×	7	71
Jihoon Tack	37 0.6×	18 0.3×	3 0.5×	2 0.3×	3 1.0×	4	45
Colin Wei	63 1.1×	28 0.5×	2 0.3×	2 0.3×	3 1.0×	7	72
Sukmin Yun	44 0.7×	35 0.6×	4 0.7×		3 1.0×	5	66

Countries citing papers authored by Arber Zela

Since Specialization

Citations

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

Fields of papers citing papers by Arber Zela

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arber Zela

This figure shows the co-authorship network connecting the top 25 collaborators of Arber Zela. A scholar is included among the top collaborators of Arber Zela based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Arber Zela. Arber Zela is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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