Marco Gori

12.7k citations
185 papers · 5.5k indexed · 1 hit paper · h-index 31

Marco Gori

165 papers receiving 5.1k citations

Hit Papers

A new model for learning in graph domains1.0k20062026201220192505007501000

Peers

Marco Gori
Comparison fields: 5 of 174
  • Artificial Intelligence 3.2k
  • Computer Vision and Pattern Recognition 1.6k
  • Signal Processing 630
  • Information Systems 1.2k
  • Statistical and Nonlinear Physics 535
Replace Markus Hagenbuchner with:
Markus Hagenbuchner Australia
Gabriele Monfardini Italy
Joshua Zhexue Huang China
Peilin Zhao China
Franco Scarselli Italy
Zhao Li China
M. Gori Italy
Cheng Yang China
Fu-Lai Chung Hong Kong
Chris Burges United States
Marco Gori relative to Markus Hagenbuchner Australia Markus Hagenbuchner's profile →
Citations per field
00.5×5.6×
Markus Hagenbuchner · 1×
Citations per year

Countries citing papers authored by Marco Gori

Since Specialization
Citations

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

Fields of papers citing papers by Marco Gori

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Marco Gori, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Marco Gori Line = papers co-authored together Marco Gori links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20254
2 20240
3 20240
4 20240
5 20235
6 20210
7 20212
8 20205
9 20190
10
Image Classification Using Deep Learning and Prior Knowledge
20184
11
Variational Laws of Visual Attention for Dynamic Scenes
201713
12
Towards Developmental AI: The paradox of Ravenous Intelligent Agents.
20111
13
Semi-supervised active learning in graphical domains
20071
14
A random-walk based scoring algorithm with application to recommender systems for large-scale e-commerce
200616
15
Investigation into the application of graph neural networks to large-scale recommender systems
20064
16
Likely-admissible and sub-symbolic heuristics
200423
17
Focus Crawling by Context Graphs
20004
18
Learning efficiently with neural networks: a theoretical comparison between structured and flat representations
20007
19
Learning in structured domains.
19991
20 199814

About Marco Gori

Marco Gori is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 185 papers that have together received 5.5k indexed citations. Recurring topics across this work include Neural Networks and Applications (62 papers), Web Data Mining and Analysis (24 papers), Machine Learning and Algorithms (19 papers), Advanced Image and Video Retrieval Techniques (16 papers), Image Retrieval and Classification Techniques (15 papers), Fuzzy Logic and Control Systems (14 papers), Topic Modeling (13 papers) and Handwritten Text Recognition Techniques (9 papers). The work is most often cited by research in Artificial Intelligence (3.2k citations), Computer Vision and Pattern Recognition (1.6k citations) and Signal Processing (630 citations). Marco Gori has collaborated with scholars based in Italy, France and Germany. Frequent co-authors include Franco Scarselli, Gabriele Monfardini, Paolo Frasconi, A. Tesi, Monica Bianchini, Michelangelo Diligenti, Marco Maggini, G. Soda, Augusto Pucci and C. Lee Giles. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Neurocomputing, Pattern Recognition Letters, Neural Networks and Machine Learning.

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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