Gabriëlle Ras

573 total citations
2 papers, 208 citations indexed

About

Gabriëlle Ras is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Health Informatics. According to data from OpenAlex, Gabriëlle Ras has authored 2 papers receiving a total of 208 indexed citations (citations by other indexed papers that have themselves been cited), including 1 paper in Computer Vision and Pattern Recognition, 1 paper in Cognitive Neuroscience and 1 paper in Health Informatics. Recurrent topics in Gabriëlle Ras's work include Adversarial Robustness in Machine Learning (1 paper), Artificial Intelligence in Healthcare and Education (1 paper) and Explainable Artificial Intelligence (XAI) (1 paper). Gabriëlle Ras is often cited by papers focused on Adversarial Robustness in Machine Learning (1 paper), Artificial Intelligence in Healthcare and Education (1 paper) and Explainable Artificial Intelligence (XAI) (1 paper). Gabriëlle Ras collaborates with scholars based in Netherlands and United States. Gabriëlle Ras's co-authors include Marcel van Gerven, Ning Xie, Derek Doran, Sander Bosch, Luca Ambrogioni, Yağmur Güçlütürk and Umut Güçlü and has published in prestigious journals such as Scientific Reports and Journal of Artificial Intelligence Research.

In The Last Decade

Gabriëlle Ras

2 papers receiving 201 citations

Peers

Gabriëlle Ras
Marco Ancona Switzerland
Haekyu Park United States
Gianni Franchi France
Negar Rostamzadeh United States
Bernd Malle Austria
Shukang Yin China
Tiago Gonçalves Portugal
Veenu Rani India
Marco Ancona Switzerland
Gabriëlle Ras
Citations per year, relative to Gabriëlle Ras Gabriëlle Ras (= 1×) peers Marco Ancona

Countries citing papers authored by Gabriëlle Ras

Since Specialization
Citations

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

Fields of papers citing papers by Gabriëlle Ras

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gabriëlle Ras

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

All Works

2 of 2 papers shown
1.
Güçlütürk, Yağmur, Luca Ambrogioni, Gabriëlle Ras, et al.. (2022). Hyperrealistic neural decoding for reconstructing faces from fMRI activations via the GAN latent space. Scientific Reports. 12(1). 141–141. 20 indexed citations
2.
Ras, Gabriëlle, Ning Xie, Marcel van Gerven, & Derek Doran. (2022). Explainable Deep Learning: A Field Guide for the Uninitiated. Journal of Artificial Intelligence Research. 73. 329–397. 188 indexed citations

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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2026