Anthony S. Maida

2.9k citations
76 papers · 1.7k indexed · 1 hit paper · h-index 14

Anthony S. Maida

75 papers receiving 1.6k citations

Hit Papers

Deep learning in spiking neural networks8142018202620202023250500750

Peers

Anthony S. Maida
Comparison fields: 5 of 125
  • Cognitive Neuroscience 608
  • Artificial Intelligence 712
  • Electrical and Electronic Engineering 786
  • Neurology 88
  • Health Information Management 48
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Citations per year

Countries citing papers authored by Anthony S. Maida

Since Specialization
Citations

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

Fields of papers citing papers by Anthony S. Maida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anthony S. Maida. 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 Anthony S. Maida. The network helps show where Anthony S. Maida may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Anthony S. Maida, 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 Anthony S. Maida Line = papers co-authored together Anthony S. Maida links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20232
3 20232
4 202212
5 201818
6
Deep learning in spiking neural networksbreakdown →
2018814
7 20176
8
Natural Image Bases to Represent Neuroimaging Data
2013114
9
Performance of generalized multilayered perceptons trained using the Levenberg-Marquardt method
20092
10 20053
11 20034
12 20025
13
Synchronized Firing in a Time-Delayed Neural Network
20011
14
Robot navigation with a polar neural map
19993
15
Knowledge Representation Requirements for Description-Based Communication.
19923
16 19912
17
A uniform architecture for rule-based meta reasoning and representation
19872
18 19871
19
Processing entailments and accessing facts in a uniform frame system
19842
20
Knowing intentional individuals, and reasoning about knowing intentional individuals
19834

About Anthony S. Maida

Anthony S. Maida is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Computer Vision and Pattern Recognition, having authored 76 papers that have together received 1.7k indexed citations. Recurring topics across this work include Neural dynamics and brain function (20 papers), Advanced Memory and Neural Computing (15 papers), Neural Networks and Applications (12 papers), Logic, Reasoning, and Knowledge (10 papers), Semantic Web and Ontologies (7 papers), Anomaly Detection Techniques and Applications (6 papers), Advanced Image Processing Techniques (5 papers) and Music and Audio Processing (4 papers). The work is most often cited by research in Cognitive Neuroscience (608 citations), Artificial Intelligence (712 citations) and Electrical and Electronic Engineering (786 citations). Anthony S. Maida has collaborated with scholars based in United States, France and Australia. Frequent co-authors include Amirhossein Tavanaei, Timothée Masquelier, Masoud Ghodrati, Saeed Reza Kheradpisheh, Stuart C. Shapiro, Ashish Gupta, Murat Seçkin Ayhan, Magdy Bayoumi, Zag ElSayed and Xiali Hei. Their work appears in journals such as SHILAP Revista de lepidopterología, Radiology and IEEE Access.

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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