Franco Scarselli

73 papers receiving 8.1k citations

Hit Papers

The Graph Neural Network Model200620262012201920082006201410002.0k3.0k4.0k5.0k

Peers

Franco Scarselli
Comparison fields: 5 of 188
  • Artificial Intelligence 4.3k
  • Computer Vision and Pattern Recognition 2.1k
  • Information Systems 1.1k
  • Statistical and Nonlinear Physics 1000
  • Computer Networks and Communications 887
Replace Gabriele Monfardini with:
Gabriele Monfardini Italy
Markus Hagenbuchner Australia
Cheng Yang China
Ah Chung Tsoi Australia
M. Gori Italy
Hiroshi Motoda Japan
Shuai Li China
Jia Wu Australia
Aditya Grover United States
Sergei Vassilvitskii United States
Franco Scarselli relative to Gabriele Monfardini Italy Gabriele Monfardini's profile →
Citations per field
00.5×7.5×
Gabriele Monfardini · 1×
Citations per year

Countries citing papers authored by Franco Scarselli

Since Specialization
Citations

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

Fields of papers citing papers by Franco Scarselli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Franco Scarselli

This figure shows the co-authorship network connecting the top 25 collaborators of Franco Scarselli. A scholar is included among the top collaborators of Franco Scarselli 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 Franco Scarselli. Franco Scarselli 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
#WorkIndexed citations
1 0
2 0
3 1
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5 2
6 1
7 4
8
Graph Neural Networks for the Prediction of Protein-Protein Interfaces.
13
9 39
10
On the complexity of shallow and deep neural network classifiers
22
11 31
12 133
13
Investigation into the application of graph neural networks to large-scale recommender systems
4
14
Graph Neural Networks for Object Localization
6
15
Two connectionist models for graph processing: An experimental comparison on relational data
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16 12
17 28
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Face Spotting in Color Images using Recursive Neural Networks
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19
A Simple Focused Crawler.
9
20 2

About Franco Scarselli

Franco Scarselli is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 77 papers that have together received 8.4k indexed citations. Recurring topics across this work include Neural Networks and Applications (20 papers), Advanced Graph Neural Networks (19 papers) and Web Data Mining and Analysis (12 papers). The work is most often cited by research in Artificial Intelligence (4.3k citations), Computer Vision and Pattern Recognition (2.1k citations) and Statistical and Nonlinear Physics (1000 citations). Franco Scarselli has collaborated with scholars based in Italy, Australia and Belgium. Frequent co-authors include Gabriele Monfardini, Ah Chung Tsoi, Markus Hagenbuchner, M. Gori, Marco Gori, Monica Bianchini, Pietro Bongini, Marco Maggini, Simone Bonechi and Paolo Andreini. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Molecular Sciences and IEEE Transactions on Medical Imaging.

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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