Irina Higgins

49 total papers · 5.4k total citations
15 papers, 1.4k citations indexed

About

Irina Higgins is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Irina Higgins has authored 15 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 6 papers in Cognitive Neuroscience. Recurrent topics in Irina Higgins's work include Advanced Memory and Neural Computing (3 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Neural dynamics and brain function (3 papers). Irina Higgins is often cited by papers focused on Advanced Memory and Neural Computing (3 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Neural dynamics and brain function (3 papers). Irina Higgins collaborates with scholars based in United Kingdom, United States and China. Irina Higgins's co-authors include Matthew Botvinick, Christopher Burgess, Alexander Lerchner, Löıc Matthey, Arka Pal, Shakir Mohamed, Xavier Glorot, Demis Hassabis, Le Chang and Doris Y. Tsao and has published in prestigious journals such as Nature Communications, PLoS ONE and Vision Research.

In The Last Decade

Irina Higgins

14 papers receiving 1.3k citations

Hit Papers

beta-VAE: Learning Basic ... 2017 2026 2020 2023 2017 250 500 750 1000

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Irina Higgins 739 617 145 136 89 15 1.4k
Alexander Lerchner 709 1.0× 613 1.0× 143 1.0× 160 1.2× 80 0.9× 15 1.4k
Löıc Matthey 704 1.0× 610 1.0× 143 1.0× 108 0.8× 82 0.9× 11 1.4k
Çaǧlar Gülçehre 1.0k 1.4× 525 0.9× 188 1.3× 84 0.6× 80 0.9× 24 1.7k
Jyri Kivinen 643 0.9× 659 1.1× 125 0.9× 58 0.4× 74 0.8× 8 1.5k
Olivier Delalleau 923 1.2× 939 1.5× 192 1.3× 54 0.4× 73 0.8× 20 1.7k
Kyunghyun Cho 968 1.3× 604 1.0× 191 1.3× 54 0.4× 84 0.9× 39 1.5k
Andrew R. Webb 632 0.9× 507 0.8× 216 1.5× 98 0.7× 159 1.8× 24 1.7k
Ivo Danihelka 857 1.2× 641 1.0× 112 0.8× 118 0.9× 65 0.7× 9 1.5k
Habiboulaye Amadou Boubacar 788 1.1× 471 0.8× 159 1.1× 180 1.3× 131 1.5× 6 1.8k
М.А. Айзерман 650 0.9× 426 0.7× 149 1.0× 52 0.4× 149 1.7× 20 1.5k

Countries citing papers authored by Irina Higgins

Since Specialization
Citations

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

Fields of papers citing papers by Irina Higgins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Irina Higgins

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

All Works

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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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