Jure Žbontar

5.8k total citations · 2 hit papers
6 papers, 1.4k citations indexed

About

Jure Žbontar is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Jure Žbontar has authored 6 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Radiology, Nuclear Medicine and Imaging, 2 papers in Artificial Intelligence and 2 papers in Biomedical Engineering. Recurrent topics in Jure Žbontar's work include Medical Imaging Techniques and Applications (2 papers), Advanced MRI Techniques and Applications (2 papers) and Statistical and numerical algorithms (1 paper). Jure Žbontar is often cited by papers focused on Medical Imaging Techniques and Applications (2 papers), Advanced MRI Techniques and Applications (2 papers) and Statistical and numerical algorithms (1 paper). Jure Žbontar collaborates with scholars based in United States, Israel and Austria. Jure Žbontar's co-authors include Blaž Zupan, Janez Demšar, Marinka Žitnik, Tomaž Curk, Lan Umek, Miha Štajdohar, Marko Toplak, Lan Žagar, Tomaž Hočevar and Martin Možina and has published in prestigious journals such as Radiology, Magnetic Resonance in Medicine and Journal of Machine Learning Research.

In The Last Decade

Jure Žbontar

6 papers receiving 1.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Orange: data mining toolbox in python

2013 1.2k citations Janez Demšar, Tomaž Curk et al. Journal of Machine Learning Research profile →
Deep Learning Reconstruction Enables Prospectively Accelerated Clinical Knee MRI

2023 69 citations Patricia M. Johnson, Dana J. Lin et al. Radiology profile →

Peers

Jure Žbontar

MB

RNMI

AI

BE

IS

Lan Žagar Slovenia

Miha Štajdohar Slovenia

Martin Možina Slovenia

Tomaž Hočevar Slovenia

Marko Toplak Slovenia

Jake Lever Canada

Laura Toloşi Germany

Ying Xue China

Tzu-Tsung Wong Taiwan

Gaurav Gupta India

Lan Žagar Slovenia

Jure Žbontar

400 ×1.7

MB

99 ×0.4

RNMI

220 ×1.0

AI

116 ×0.8

BE

99 ×1.0

IS

Citations per year, relative to Jure Žbontar Jure Žbontar (= 1×) peers Lan Žagar

Countries citing papers authored by Jure Žbontar

Since Specialization

Citations

This map shows the geographic impact of Jure Žbontar'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 Jure Žbontar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jure Žbontar more than expected).

Fields of papers citing papers by Jure Žbontar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jure Žbontar. 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 Jure Žbontar. The network helps show where Jure Žbontar may publish in the future.

Co-authorship network of co-authors of Jure Žbontar

This figure shows the co-authorship network connecting the top 25 collaborators of Jure Žbontar. A scholar is included among the top collaborators of Jure Žbontar 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 Jure Žbontar. Jure Žbontar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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6 of 6 papers shown

1.

Johnson, Patricia M., Dana J. Lin, Jure Žbontar, et al.. (2023). Deep Learning Reconstruction Enables Prospectively Accelerated Clinical Knee MRI. Radiology. 307(2). e220425–e220425. 69 indexed citations breakdown →

2.

Žbontar, Jure, Jing Li, Ishan Misra, Yann LeCun, & Stéphane Deny. (2021). Barlow Twins: Self-Supervised Learning via Redundancy Reduction. International Conference on Machine Learning. 12310–12320. 3 indexed citations

3.

Defazio, Aaron, Mark Tygert, Rachel Ward, & Jure Žbontar. (2021). Compressed sensing with a jackknife and a bootstrap. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

4.

Defazio, Aaron, Mark Tygert, Rachel Ward, & Jure Žbontar. (2021). Compressed sensing with a jackknife, a bootstrap, and visualization. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

5.

Knöll, Florian, Tullie Murrell, Anuroop Sriram, et al.. (2020). Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge. Magnetic Resonance in Medicine. 84(6). 3054–3070. 128 indexed citations

6.

Demšar, Janez, Tomaž Curk, Tomaž Hočevar, et al.. (2013). Orange: data mining toolbox in python. Journal of Machine Learning Research. 14(1). 2349–2353. 1239 indexed citations breakdown →

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.

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