Francesco Visin

2.0k total citations
4 papers, 87 citations indexed

About

Francesco Visin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Francesco Visin has authored 4 papers receiving a total of 87 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Francesco Visin's work include Domain Adaptation and Few-Shot Learning (2 papers), Cancer-related molecular mechanisms research (1 paper) and Multimodal Machine Learning Applications (1 paper). Francesco Visin is often cited by papers focused on Domain Adaptation and Few-Shot Learning (2 papers), Cancer-related molecular mechanisms research (1 paper) and Multimodal Machine Learning Applications (1 paper). Francesco Visin collaborates with scholars based in United Kingdom, United States and Romania. Francesco Visin's co-authors include Razvan Pascanu, Raia Hadsell, David Vázquez, Faruk Ahmed, Ishaan Gulrajani, Kundan Kumar, Aaron Courville, Andrei Rusu, Dushyant Rao and Yee Whye Teh and has published in prestigious journals such as Research Explorer (The University of Manchester) and arXiv (Cornell University).

In The Last Decade

Francesco Visin

4 papers receiving 83 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Francesco Visin United Kingdom	4	70	49	5	5	4	4	87
Orestis Plevrakis United States	2	84 1.2×	51 1.0×	5 1.0×	4 0.8×	4 1.0×	2	113
Ousmane Dia United States	3	79 1.1×	35 0.7×	9 1.8×	7 1.4×	7 1.8×	5	95
Jaesik Yoon Netherlands	3	73 1.0×	36 0.7×	8 1.6×	7 1.4×	1 0.3×	5	86
Rosanne Liu United States	3	73 1.0×	82 1.7×	13 2.6×	2 0.4×	2 0.5×	5	121
Shiv Shankar India	4	59 0.8×	48 1.0×	3 0.6×	4 0.8×		7	80
Zikang Liu China	3	56 0.8×	61 1.2×	6 1.2×		2 0.5×	11	105
Emilie Morvant France	6	55 0.8×	18 0.4×	2 0.4×	3 0.6×	2 0.5×	10	69
Amjad Almahairi United States	6	80 1.1×	85 1.7×	6 1.2×	2 0.4×	1 0.3×	10	135
Gowthami Somepalli United States	2	31 0.4×	36 0.7×	2 0.4×	2 0.4×	6 1.5×	2	71
Lewei Lu China	1	43 0.6×	53 1.1×	10 2.0×		4 1.0×	3	105

Countries citing papers authored by Francesco Visin

Since Specialization

Citations

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

Fields of papers citing papers by Francesco Visin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesco Visin

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

All Works

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4 of 4 papers shown

1.

Rusu, Andrei A., et al.. (2020). Meta-Learning with Warped Gradient Descent. Research Explorer (The University of Manchester). 20 indexed citations

2.

Bornschein, Jörg, Francesco Visin, & Simon Osindero. (2020). Small Data, Big Decisions: Model Selection in the Small-Data Regime. arXiv (Cornell University). 1. 1035–1044. 6 indexed citations

3.

Rao, Dushyant, Francesco Visin, Andrei Rusu, et al.. (2019). Continual Unsupervised Representation Learning. arXiv (Cornell University). 32. 7645–7655. 26 indexed citations

4.

Gulrajani, Ishaan, Kundan Kumar, Faruk Ahmed, et al.. (2016). PixelVAE: A Latent Variable Model for Natural Images. arXiv (Cornell University). 35 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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