Julien Cornebise
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Statistics and Probability top 5%
- Biomedical Engineering
- Co-authors
- Daan WierstraCharles BlundellKoray KavukcuogluDiana MateusJaime S. CardosoJacinto C. NascimentoAndrew P. BradleyZhi Lü
- Topics
- Bayesian Methods and Mixture Models (4 papers)Statistical Methods and Bayesian Inference (2 papers)Target Tracking and Data Fusion in Sensor Networks (2 papers)
- Partner nations
- United KingdomAustraliaSweden
In The Last Decade
Julien Cornebise
8 papers receiving 767 citations
Hit Papers
Peers
Comparison fields: 5 of 120
- Artificial Intelligence 424
- Computer Vision and Pattern Recognition 265
- Radiology, Nuclear Medicine and Imaging 161
- Statistics and Probability 75
- Biomedical Engineering 45
Countries citing papers authored by Julien Cornebise
This map shows the geographic impact of Julien Cornebise'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 Julien Cornebise with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julien Cornebise more than expected).
Fields of papers citing papers by Julien Cornebise
This network shows the impact of papers produced by Julien Cornebise. 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 Julien Cornebise. The network helps show where Julien Cornebise may publish in the future.
Co-authorship network of co-authors of Julien Cornebise
This figure shows the co-authorship network connecting the top 25 collaborators of Julien Cornebise. A scholar is included among the top collaborators of Julien Cornebise 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 Julien Cornebise. Julien Cornebise is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Reproducibility and Stability Analysis in Metric-Based Few-Shot Learning. | 1 |
| 2 | HighRes-net: Multi-Frame Super-Resolution by Recursive Fusion | 5 |
| 3 | 289 | |
| 4 | Weight Uncertainty in Neural Networkbreakdown → | 363 |
| 5 | 70 | |
| 6 | 5 | |
| 7 | 14 | |
| 8 | 40 |
About Julien Cornebise
Julien Cornebise is a scholar working on Statistics and Probability, Artificial Intelligence and Neurology, having authored 8 papers that have together received 787 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (4 papers), Statistical Methods and Bayesian Inference (2 papers) and Target Tracking and Data Fusion in Sensor Networks (2 papers). The work is most often cited by research in Artificial Intelligence (424 citations), Computer Vision and Pattern Recognition (265 citations) and Statistics and Probability (75 citations). Julien Cornebise has collaborated with scholars based in United Kingdom, Australia and Sweden. Frequent co-authors include Daan Wierstra, Charles Blundell, Koray Kavukcuoglu, Diana Mateus, Jaime S. Cardoso, Jacinto C. Nascimento, Andrew P. Bradley, Zhi Lü, Vasileios Belagiannis and Marco Loog. Their work appears in journals such as Statistics in Medicine, Lecture notes in computer science and Statistics and Computing.
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.