Jérôme Rony

415 total citations
9 papers, 108 citations indexed

About

Jérôme Rony is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jérôme Rony has authored 9 papers receiving a total of 108 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 3 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jérôme Rony's work include Adversarial Robustness in Machine Learning (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and AI in cancer detection (2 papers). Jérôme Rony is often cited by papers focused on Adversarial Robustness in Machine Learning (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and AI in cancer detection (2 papers). Jérôme Rony collaborates with scholars based in Canada, France and Italy. Jérôme Rony's co-authors include Ismail Ben Ayed, José Dolz, Éric Granger, Soufiane Belharbi, Luke McCaffrey, Pablo Piantanida, Jean‐Christophe Pesquet, Fabio Roli, Luca Demetrio and Battista Biggio and has published in prestigious journals such as IEEE Transactions on Medical Imaging, arXiv (Cornell University) and TECNALIA Publications (Fundación TECNALIA Research & Innovation).

In The Last Decade

Jérôme Rony

9 papers receiving 103 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jérôme Rony Canada	6	85	45	35	11	6	9	108
Maximilian Ilse Netherlands	5	96 1.1×	74 1.6×	58 1.7×	10 0.9×	7 1.2×	7	166
Chaofan Tao Hong Kong	6	122 1.4×	64 1.4×	30 0.9×	4 0.4×	3 0.5×	12	169
Ashish Arora United States	6	41 0.5×	33 0.7×	20 0.6×	19 1.7×	3 0.5×	12	83
Olivia Wiles United Kingdom	5	31 0.4×	42 0.9×	20 0.6×	15 1.4×	5 0.8×	7	101
Yuting Xiao China	4	71 0.8×	66 1.5×	45 1.3×	3 0.3×		7	142
Martin Hedlund Sweden	6	62 0.7×	38 0.8×	37 1.1×	2 0.2×	7 1.2×	13	96
Ping Luo China	5	49 0.6×	61 1.4×	11 0.3×	14 1.3×	3 0.5×	10	136
Yujing Ma China	5	45 0.5×	25 0.6×	34 1.0×	4 0.4×	2 0.3×	7	99
Leonardo O. Iheme Türkiye	5	54 0.6×	16 0.4×	26 0.7×	7 0.6×	2 0.3×	13	82
Jeffrey De Fauw United States	2	47 0.6×	63 1.4×	9 0.3×	6 0.5×	1 0.2×	3	102

Countries citing papers authored by Jérôme Rony

Since Specialization

Citations

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

Fields of papers citing papers by Jérôme Rony

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jérôme Rony

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

All Works

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9 of 9 papers shown

1.

Rony, Jérôme, Maura Pintor, Luca Demetrio, et al.. (2025). AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples. Proceedings of the AAAI Conference on Artificial Intelligence. 39(3). 2600–2608. 5 indexed citations

2.

Rony, Jérôme, Soufiane Belharbi, José Dolz, et al.. (2023). Deep Weakly-Supervised Learning Methods for Classification and Localization in Histology Images: A Survey. arXiv (Cornell University). 2(March 2023). 96–150. 13 indexed citations

3.

Rony, Jérôme, Jean‐Christophe Pesquet, & Ismail Ben Ayed. (2023). Proximal Splitting Adversarial Attack for Semantic Segmentation. SPIRE - Sciences Po Institutional REpository. 20524–20533. 9 indexed citations

4.

Rony, Jérôme, et al.. (2023). Class Adaptive Network Calibration. TECNALIA Publications (Fundación TECNALIA Research & Innovation). 16070–16079. 5 indexed citations

5.

Belharbi, Soufiane, Jérôme Rony, José Dolz, et al.. (2021). Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty. IEEE Transactions on Medical Imaging. 41(3). 702–714. 39 indexed citations

6.

Rony, Jérôme, et al.. (2020). Metric learning: cross-entropy vs. pairwise losses. arXiv (Cornell University). 3 indexed citations

7.

Rony, Jérôme, et al.. (2020). Information Maximization for Few-Shot Learning. Neural Information Processing Systems. 33. 2445–2457. 32 indexed citations

8.

Belharbi, Soufiane, Jérôme Rony, José Dolz, et al.. (2019). Weakly Supervised Object Localization using Min-Max Entropy: an Interpretable Framework.. arXiv (Cornell University). 1 indexed citations

9.

Rony, Jérôme, et al.. (2018). Decoupling direction and norm for efficient gradient-based l2 adversarial attacks. Espace ÉTS (ETS). 1 indexed citations

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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