Eugene Belilovsky

1.5k total citations
21 papers, 285 citations indexed

About

Eugene Belilovsky is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Eugene Belilovsky has authored 21 papers receiving a total of 285 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 13 papers in Artificial Intelligence and 3 papers in Cognitive Neuroscience. Recurrent topics in Eugene Belilovsky's work include Domain Adaptation and Few-Shot Learning (8 papers), Multimodal Machine Learning Applications (5 papers) and Sparse and Compressive Sensing Techniques (3 papers). Eugene Belilovsky is often cited by papers focused on Domain Adaptation and Few-Shot Learning (8 papers), Multimodal Machine Learning Applications (5 papers) and Sparse and Compressive Sensing Techniques (3 papers). Eugene Belilovsky collaborates with scholars based in Canada, France and United States. Eugene Belilovsky's co-authors include Rahaf Aljundi, M. Caccia, Laurent Charlin, Tinne Tuytelaars, Min Lin, Matthew B. Blaschko, Sergey Zagoruyko, Nikos Komodakis, Simon Lacoste-Julien and Edouard Oyallon and has published in prestigious journals such as Cell, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.

In The Last Decade

Eugene Belilovsky

19 papers receiving 280 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eugene Belilovsky Canada 9 200 155 33 20 17 21 285
Eden Belouadah France 3 266 1.3× 160 1.0× 33 1.0× 6 0.3× 12 0.7× 5 318
Nan Song China 5 182 0.9× 114 0.7× 29 0.9× 6 0.3× 5 0.3× 15 263
Xinyuan Chang China 6 332 1.7× 247 1.6× 53 1.6× 5 0.3× 8 0.5× 8 430
Kaizhu Huang China 8 189 0.9× 214 1.4× 25 0.8× 6 0.3× 12 0.7× 12 316
Songlin Dong China 9 392 2.0× 232 1.5× 59 1.8× 6 0.3× 11 0.6× 19 482
Sayna Ebrahimi United States 7 144 0.7× 109 0.7× 21 0.6× 6 0.3× 14 0.8× 10 241
Hyun-Soo Kim South Korea 2 106 0.5× 317 2.0× 24 0.7× 9 0.5× 7 0.4× 3 395
Zhihe Lu China 8 263 1.3× 384 2.5× 37 1.1× 6 0.3× 8 0.5× 16 458

Countries citing papers authored by Eugene Belilovsky

Since Specialization
Citations

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

Fields of papers citing papers by Eugene Belilovsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eugene Belilovsky

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

All Works

20 of 20 papers shown
1.
Eickenberg, Michael, et al.. (2025). Unsupervised Test-Time Adaptation for Hepatic Steatosis Grading Using Ultrasound B-Mode Images. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 72(5). 601–611. 1 indexed citations
2.
Reddy, Siva, et al.. (2025). Large language models deconstruct the clinical intuition behind diagnosing autism. Cell. 188(8). 2235–2248.e10. 5 indexed citations
3.
Eickenberg, Michael, et al.. (2024). Adversarial Attacks on the Interpretation of Neuron Activation Maximization. Proceedings of the AAAI Conference on Artificial Intelligence. 38(5). 4315–4324.
4.
Qi, Yue, Alexandre Cadrin-Chênevert, Emmanuel Montagnon, et al.. (2024). Simulating federated learning for steatosis detection using ultrasound images. Scientific Reports. 14(1). 13253–13253. 7 indexed citations
5.
Wolf, Guy, et al.. (2024). Non-Uniform Parameter-Wise Model Merging. 5946–5954.
6.
Ravanelli, Mirco, et al.. (2023). Simulated Annealing in Early Layers Leads to Better Generalization. 20205–20214. 5 indexed citations
7.
Kulbay, Merve, M.A. Chaudary, Samuel Kadoury, et al.. (2023). Automated liver segmentation and steatosis grading using deep learning on B-mode ultrasound images. PolyPublie (École Polytechnique de Montréal). 1–4. 1 indexed citations
8.
Mudur, Sudhir P., et al.. (2022). Probing Representation Forgetting in Supervised and Unsupervised Continual Learning. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 16691–16700. 25 indexed citations
9.
Desrosiers, Christian, et al.. (2022). Revisiting Learnable Affines for Batch Norm in Few-Shot Transfer Learning. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 9099–9108. 16 indexed citations
10.
Rish, Irina, et al.. (2022). Parametric Scattering Networks. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 5739–5748. 10 indexed citations
11.
Knyazev, B. A., Harm de Vries, Cătălina Cangea, et al.. (2021). Generative Compositional Augmentations for Scene Graph Prediction. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 15807–15817. 16 indexed citations
12.
Knyazev, B. A., Harm de Vries, Cătălina Cangea, et al.. (2020). Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation. 2 indexed citations
13.
Caccia, Lucas, Eugene Belilovsky, Massimo Caccia, & Joëlle Pineau. (2019). Online Learned Continual Compression with Stacked Quantization Module.. arXiv (Cornell University). 1 indexed citations
14.
Aljundi, Rahaf, Eugene Belilovsky, Tinne Tuytelaars, et al.. (2019). Online Continual Learning with Maximal Interfered Retrieval. arXiv (Cornell University). 32. 11849–11860. 109 indexed citations
15.
Oyallon, Edouard, Sergey Zagoruyko, Nikos Komodakis, et al.. (2018). Scattering Networks for Hybrid Representation Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 41(9). 2208–2221. 40 indexed citations
16.
Belilovsky, Eugene, Michael Eickenberg, & Edouard Oyallon. (2018). Shallow Learning For Deep Networks. 1 indexed citations
17.
Belilovsky, Eugene, et al.. (2016). A Test of Relative Similarity For Model Selection in Generative Models. Lirias (KU Leuven). 14 indexed citations
18.
Belilovsky, Eugene, Anna B. Konova, Jean Honorio, et al.. (2015). Predictive sparse modeling of fMRI data for improved classification, regression, and visualization using the k -support norm. Computerized Medical Imaging and Graphics. 46. 40–46. 13 indexed citations
19.
Belilovsky, Eugene, Andreas A. Argyriou, Gaël Varoquaux, & Matthew B. Blaschko. (2015). Convex relaxations of penalties for sparse correlated variables with bounded total variation. Machine Learning. 100(2-3). 533–553. 5 indexed citations
20.
Müller, Florian, Eugene Belilovsky, & Alfred Mertins. (2009). Generalized cyclic transformations in speaker-independent speech recognition. 1. 211–215. 3 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Eden Belouadah Breakdown of academic impact, for papers by Nan Song Breakdown of academic impact, for papers by Xinyuan Chang Breakdown of academic impact, for papers by Kaizhu Huang Breakdown of academic impact, for papers by Songlin Dong Breakdown of academic impact, for papers by Sayna Ebrahimi Breakdown of academic impact, for papers by Hyun-Soo Kim Breakdown of academic impact, for papers by Zhihe Lu
Rankless by CCL
2026