Arber Zela
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Materials Chemistry
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Frank HutterThomas ElskenThomas BroxYassine MarrakchiTonmoy SaikiaRohit MohanBenedikt StafflerAbhinav Valada
- Topics
- Advanced Neural Network Applications (3 papers)Domain Adaptation and Few-Shot Learning (3 papers)Adversarial Robustness in Machine Learning (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputer Science Applications
- Journals
- International Journal of Computer VisionJournal of Clinical MedicinearXiv (Cornell University)
- Partner nations
- GermanySwitzerlandIndia
In The Last Decade
Arber Zela
4 papers receiving 73 citations
Peers
Comparison fields: 5 of 25
- Artificial Intelligence 60
- Computer Vision and Pattern Recognition 55
- Electrical and Electronic Engineering 6
- Materials Chemistry 6
- Radiology, Nuclear Medicine and Imaging 3
Countries citing papers authored by Arber Zela
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 11 | |
| 3 | NASLib: A Modular and Flexible Neural Architecture Search Library | 3 |
| 4 | Understanding and Robustifying Differentiable Architecture Search | 41 |
| 5 | 23 |
About Arber Zela
Arber Zela is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Materials Chemistry, having authored 5 papers that have together received 78 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (3 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Adversarial Robustness in Machine Learning (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (55 citations), Artificial Intelligence (60 citations) and Computer Science Applications (2 citations). Arber Zela has collaborated with scholars based in Germany, Switzerland and India. Frequent co-authors include Frank Hutter, Thomas Elsken, Thomas Brox, Yassine Marrakchi, Tonmoy Saikia, Rohit Mohan, Benedikt Staffler, Abhinav Valada, Jan Hendrik Metzen and Josif Grabocka. Their work appears in journals such as International Journal of Computer Vision, Journal of Clinical Medicine 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.