Ryan G. Gomes

424 citations
4 papers · 230 indexed · h-index 4
Topics
Bayesian Methods and Mixture Models (2 papers)Machine Learning and Algorithms (2 papers)Image Retrieval and Classification Techniques (1 paper)
Journals
Neural Information Processing SystemsInternational Conference on Machine Learning
Partner nations
United States

In The Last Decade

Ryan G. Gomes

4 papers receiving 220 citations

Peers

Ryan G. Gomes
Comparison fields: 5 of 52
  • Artificial Intelligence 163
  • Computer Vision and Pattern Recognition 117
  • Computational Theory and Mathematics 21
  • Signal Processing 20
  • Computer Networks and Communications 14
Replace J. Bins with:
J. Bins Brazil
Sushanta Biswas India
Aydın Ulaş Türkiye
Maxinder S Kanwal Poland
Emmanuel Bengio Canada
Jiajun Liu China
H. Selvaraj United States
Linnan Wang United States
Douglas R. Heisterkamp United States
Xianzhong Long China
Ryan G. Gomes relative to J. Bins Brazil J. Bins's profile →
Citations per field
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Countries citing papers authored by Ryan G. Gomes

Since Specialization
Citations

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

Fields of papers citing papers by Ryan G. Gomes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryan G. Gomes. 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 Ryan G. Gomes. The network helps show where Ryan G. Gomes may publish in the future.

Co-authorship network of co-authors of Ryan G. Gomes

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

All Works

4 of 4 papers shown
#WorkIndexed citations
1
Budgeted Nonparametric Learning from Data Streams
39
2
Discriminative Clustering by Regularized Information Maximization
151
3 6
4 34

About Ryan G. Gomes

Ryan G. Gomes is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Infectious Diseases, having authored 4 papers that have together received 230 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (2 papers), Machine Learning and Algorithms (2 papers) and Image Retrieval and Classification Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (117 citations), Artificial Intelligence (163 citations) and Signal Processing (20 citations). Ryan G. Gomes has collaborated with scholars based in United States. Frequent co-authors include Andreas Krause, Pietro Perona and Max Welling. Their work appears in journals such as Neural Information Processing Systems and International Conference on 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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