Rudy Bunel
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Software top 10%
- Hardware and Architecture
- Co-authors
- Pushmeet KohliPhilip H. S. TorrKrishnamurthy DvijothamJonathan UesatoRobert StanforthChongli QinSven GowalTimothy Mann
- Topics
- Adversarial Robustness in Machine Learning (7 papers)Domain Adaptation and Few-Shot Learning (3 papers)Software Testing and Debugging Techniques (3 papers)
- Journals
- SIAM Journal on Imaging SciencesIEEE Control Systems LettersInfoscience (Ecole Polytechnique Fédérale de Lausanne)
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Rudy Bunel
12 papers receiving 168 citations
Peers
Comparison fields: 5 of 41
- Artificial Intelligence 145
- Computer Vision and Pattern Recognition 52
- Electrical and Electronic Engineering 25
- Software 22
- Hardware and Architecture 16
Countries citing papers authored by Rudy Bunel
This map shows the geographic impact of Rudy Bunel'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 Rudy Bunel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rudy Bunel more than expected).
Fields of papers citing papers by Rudy Bunel
This network shows the impact of papers produced by Rudy Bunel. 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 Rudy Bunel. The network helps show where Rudy Bunel may publish in the future.
Co-authorship network of co-authors of Rudy Bunel
This figure shows the co-authorship network connecting the top 25 collaborators of Rudy Bunel. A scholar is included among the top collaborators of Rudy Bunel 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 Rudy Bunel. Rudy Bunel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | Scaling the Convex Barrier with Active Sets | 5 |
| 3 | 2 | |
| 4 | An efficient nonconvex reformulation of stagewise convex optimization problems | 1 |
| 5 | 64 | |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 17 | |
| 9 | Piecewise Linear Neural Networks verification: A comparative study | 16 |
| 10 | 4 | |
| 11 | 51 | |
| 12 | Adaptive neural compilation | 4 |
| 13 | Learning to superoptimize programs | 3 |
About Rudy Bunel
Rudy Bunel is a scholar working on Software, Artificial Intelligence and Hardware and Architecture, having authored 13 papers that have together received 175 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (7 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Software Testing and Debugging Techniques (3 papers). The work is most often cited by research in Software (22 citations), Artificial Intelligence (145 citations) and Computer Vision and Pattern Recognition (52 citations). Rudy Bunel has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Pushmeet Kohli, Philip H. S. Torr, Krishnamurthy Dvijotham, Jonathan Uesato, Robert Stanforth, Chongli Qin, Sven Gowal, Timothy Mann, Relja Arandjelović and Philip H. S. Torr. Their work appears in journals such as SIAM Journal on Imaging Sciences, IEEE Control Systems Letters and Infoscience (Ecole Polytechnique Fédérale de Lausanne).
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.