Yiğitcan Kaya
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Signal Processing
- Hardware and Architecture
- Co-authors
- Tudor DumitraşSanghyun HongCristiano GiuffridaPietro FrigoYizheng ChenMarcus BotacinDavid WagnerFabio Pierazzi
- Topics
- Adversarial Robustness in Machine Learning (4 papers)Anomaly Detection Techniques and Applications (3 papers)Explainable Artificial Intelligence (XAI) (2 papers)
- Journals
- arXiv (Cornell University)International Conference on Machine Learning
- Partner nations
- United StatesNetherlandsUnited Kingdom
In The Last Decade
Yiğitcan Kaya
6 papers receiving 60 citations
Peers
Comparison fields: 5 of 19
- Artificial Intelligence 48
- Computer Vision and Pattern Recognition 21
- Electrical and Electronic Engineering 18
- Signal Processing 15
- Hardware and Architecture 11
Countries citing papers authored by Yiğitcan Kaya
This map shows the geographic impact of Yiğitcan Kaya'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 Yiğitcan Kaya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yiğitcan Kaya more than expected).
Fields of papers citing papers by Yiğitcan Kaya
This network shows the impact of papers produced by Yiğitcan Kaya. 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 Yiğitcan Kaya. The network helps show where Yiğitcan Kaya may publish in the future.
Co-authorship network of co-authors of Yiğitcan Kaya
This figure shows the co-authorship network connecting the top 25 collaborators of Yiğitcan Kaya. A scholar is included among the top collaborators of Yiğitcan Kaya 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 Yiğitcan Kaya. Yiğitcan Kaya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | When Does Data Augmentation Help With Membership Inference Attacks | 7 |
| 3 | A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference | 2 |
| 4 | 30 | |
| 5 | Shallow-Deep Networks: Understanding and Mitigating Network Overthinking | 18 |
| 6 | How to Stop Off-the-Shelf Deep Neural Networks from Overthinking. | 3 |
About Yiğitcan Kaya
Yiğitcan Kaya is a scholar working on Artificial Intelligence, Signal Processing and Management Science and Operations Research, having authored 6 papers that have together received 61 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (4 papers), Anomaly Detection Techniques and Applications (3 papers) and Explainable Artificial Intelligence (XAI) (2 papers). The work is most often cited by research in Hardware and Architecture (11 citations), Artificial Intelligence (48 citations) and Signal Processing (15 citations). Yiğitcan Kaya has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Tudor Dumitraş, Sanghyun Hong, Cristiano Giuffrida, Pietro Frigo, Yizheng Chen, Marcus Botacin, David Wagner, Fabio Pierazzi and Lorenzo Cavallaro. Their work appears in journals such as arXiv (Cornell University) and International Conference on Machine Learning.
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.