Arnaud Bergeron

1.4k total citations
4 papers, 203 citations indexed

About

Arnaud Bergeron is a scholar working on Artificial Intelligence, Hardware and Architecture and Computer Vision and Pattern Recognition. According to data from OpenAlex, Arnaud Bergeron has authored 4 papers receiving a total of 203 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 2 papers in Hardware and Architecture and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Arnaud Bergeron's work include Computational Physics and Python Applications (2 papers), Parallel Computing and Optimization Techniques (2 papers) and Fuel Cells and Related Materials (1 paper). Arnaud Bergeron is often cited by papers focused on Computational Physics and Python Applications (2 papers), Parallel Computing and Optimization Techniques (2 papers) and Fuel Cells and Related Materials (1 paper). Arnaud Bergeron collaborates with scholars based in Canada, Germany and France. Arnaud Bergeron's co-authors include Pascal Lamblin, Olivier Breuleux, Yoshua Bengio, Frédéric Bastien, Razvan Pascanu, Guillaume Desjardins, Ian Goodfellow, James Bergstra, David Warde-Farley and Olivier Delalleau and has published in prestigious journals such as arXiv (Cornell University).

In The Last Decade

Arnaud Bergeron

4 papers receiving 192 citations

Peers

Arnaud Bergeron
Feihu Huang United States
S. Y. Lu United States
Roi Livni Israel
Qian Guo China
Arnaud Bergeron
Citations per year, relative to Arnaud Bergeron Arnaud Bergeron (= 1×) peers Mathias Berglund

Countries citing papers authored by Arnaud Bergeron

Since Specialization
Citations

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

Fields of papers citing papers by Arnaud Bergeron

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arnaud Bergeron

This figure shows the co-authorship network connecting the top 25 collaborators of Arnaud Bergeron. A scholar is included among the top collaborators of Arnaud Bergeron 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 Arnaud Bergeron. Arnaud Bergeron 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
1.
Merriënboer, Bart van, Olivier Breuleux, Arnaud Bergeron, & Pascal Lamblin. (2018). Automatic differentiation in ML: Where we are and where we should be going. arXiv (Cornell University). 31. 8757–8767. 25 indexed citations
2.
Bergstra, James, Frédéric Bastien, Olivier Breuleux, et al.. (2012). Theano: Deep Learning on GPUs with Python. 125 indexed citations
3.
Bengio, Yoshua, Frédéric Bastien, Arnaud Bergeron, et al.. (2011). Deep Learners Benefit More from Out-of-Distribution Examples. 164–172. 52 indexed citations
4.
Bastien, Frédéric, Arnaud Bergeron, Pascal Vincent, & Yoshua Bengio. (2011). A Common GPU n-Dimensional Array for Python and C. 1 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026