Yunus Saatçi
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Signal Processing top 10%
- Statistics and Probability top 10%
- Control and Systems Engineering
- Co-authors
- Christopher TownJurgen Van GaelYee Whye TehZoubin GhahramaniR.D. TurnerCarl Edward RasmussenAndrew Gordon WilsonJohn P. Cunningham
- Topics
- Gaussian Processes and Bayesian Inference (2 papers)Emotion and Mood Recognition (1 paper)Bayesian Methods and Mixture Models (1 paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligencePhilosophical Transactions of the Royal Society A Mathematical Physical and Engineering SciencesNeural Information Processing Systems
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Yunus Saatçi
6 papers receiving 348 citations
Peers
Comparison fields: 5 of 86
- Artificial Intelligence 193
- Computer Vision and Pattern Recognition 109
- Signal Processing 86
- Statistics and Probability 37
- Control and Systems Engineering 30
Countries citing papers authored by Yunus Saatçi
This map shows the geographic impact of Yunus Saatçi'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 Yunus Saatçi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yunus Saatçi more than expected).
Fields of papers citing papers by Yunus Saatçi
This network shows the impact of papers produced by Yunus Saatçi. 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 Yunus Saatçi. The network helps show where Yunus Saatçi may publish in the future.
Co-authorship network of co-authors of Yunus Saatçi
This figure shows the co-authorship network connecting the top 25 collaborators of Yunus Saatçi. A scholar is included among the top collaborators of Yunus Saatçi 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 Yunus Saatçi. Yunus Saatçi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Bayesian GAN | 20 |
| 2 | 29 | |
| 3 | Gaussian Process Change Point Models | 79 |
| 4 | 9 | |
| 5 | 155 | |
| 6 | 83 |
About Yunus Saatçi
Yunus Saatçi is a scholar working on Statistics and Probability, Transportation and Artificial Intelligence, having authored 6 papers that have together received 375 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (2 papers), Emotion and Mood Recognition (1 paper) and Bayesian Methods and Mixture Models (1 paper). The work is most often cited by research in Signal Processing (86 citations), Artificial Intelligence (193 citations) and Computer Vision and Pattern Recognition (109 citations). Yunus Saatçi has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Christopher Town, Jurgen Van Gael, Yee Whye Teh, Zoubin Ghahramani, R.D. Turner, Carl Edward Rasmussen, Andrew Gordon Wilson, John P. Cunningham, Elad Gilboa and Richard Gibbens. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences and Neural Information Processing Systems.
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.