Cătălina Cangea

484 total citations
5 papers, 68 citations indexed

About

Cătălina Cangea is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Cătălina Cangea has authored 5 papers receiving a total of 68 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Computational Theory and Mathematics. Recurrent topics in Cătălina Cangea's work include Multimodal Machine Learning Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Complex Network Analysis Techniques (1 paper). Cătălina Cangea is often cited by papers focused on Multimodal Machine Learning Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Complex Network Analysis Techniques (1 paper). Cătălina Cangea collaborates with scholars based in United Kingdom and Canada. Cătălina Cangea's co-authors include Píetro Lió, Petar Veličković, Cristian Bodnar, Eugene Belilovsky, B. A. Knyazev, Graham W. Taylor, Harm de Vries, Aaron Courville, Tom L. Blundell and Arian R. Jamasb and has published in prestigious journals such as Methods in molecular biology, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and IRIS Research product catalog (Sapienza University of Rome).

In The Last Decade

Cătălina Cangea

5 papers receiving 67 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Cătălina Cangea United Kingdom	4	36	33	16	13	13	5	68
Lukas Schott Germany	4	61 1.7×	27 0.8×	9 0.6×	10 0.8×	2 0.2×	4	90
Mozhdeh Gheini United States	2	31 0.9×	22 0.7×	7 0.4×	4 0.3×	4 0.3×	5	74
Sjoerd van Steenkiste Switzerland	6	56 1.6×	69 2.1×	3 0.2×	5 0.4×	5 0.4×	14	117
Matan Eyal Israel	5	85 2.4×	13 0.4×	16 1.0×	6 0.5×	4 0.3×	9	101
Yonatan Geifman Israel	4	66 1.8×	26 0.8×	3 0.2×	7 0.5×	3 0.2×	6	85
Tri Dao United States	6	37 1.0×	20 0.6×	18 1.1×	4 0.3×	2 0.2×	12	74
Aohan Zeng China	4	49 1.4×	14 0.4×	15 0.9×	4 0.3×	4 0.3×	6	76
Nikolay Nikolov Bulgaria	3	58 1.6×	25 0.8×	7 0.4×	3 0.2×	6 0.5×	3	63
Virginie Lallemand France	3	63 1.8×	49 1.5×	3 0.2×	13 1.0×	5 0.4×	10	69
Nathan Schucher Canada	2	32 0.9×	52 1.6×	5 0.3×	6 0.5×	2 0.2×	2	79

Countries citing papers authored by Cătălina Cangea

Since Specialization

Citations

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

Fields of papers citing papers by Cătălina Cangea

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cătălina Cangea

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

All Works

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5 of 5 papers shown

1.

Jamasb, Arian R., Ben Day, Cătălina Cangea, Píetro Lió, & Tom L. Blundell. (2021). Deep Learning for Protein–Protein Interaction Site Prediction. Methods in molecular biology. 2361. 263–288. 12 indexed citations

2.

Bodnar, Cristian, Cătălina Cangea, & Píetro Lió. (2021). Deep Graph Mapper: Seeing Graphs Through the Neural Lens. IRIS Research product catalog (Sapienza University of Rome). 16 indexed citations

3.

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

4.

Cangea, Cătălina, Petar Veličković, & Píetro Lió. (2020). XFlow: Cross-Modal Deep Neural Networks for Audiovisual Classification. IRIS Research product catalog (Sapienza University of Rome). 22 indexed citations

5.

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

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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