Mehdi Mirza

29.4k total citations · 3 hit papers
5 papers, 9.2k citations indexed

About

Mehdi Mirza is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Statistical and Nonlinear Physics. According to data from OpenAlex, Mehdi Mirza has authored 5 papers receiving a total of 9.2k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 1 paper in Statistical and Nonlinear Physics. Recurrent topics in Mehdi Mirza's work include Domain Adaptation and Few-Shot Learning (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Emotion and Mood Recognition (1 paper). Mehdi Mirza is often cited by papers focused on Domain Adaptation and Few-Shot Learning (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Emotion and Mood Recognition (1 paper). Mehdi Mirza collaborates with scholars based in Canada, France and Germany. Mehdi Mirza's co-authors include Yoshua Bengio, Aaron Courville, Ian Goodfellow, David Warde-Farley, Sherjil Ozair, Bing Xu, Jean Pouget-Abadie, Xiao Da, Sébastien Jean and Nicolas Boulanger-Lewandowski and has published in prestigious journals such as Communications of the ACM, Journal on Multimodal User Interfaces and arXiv (Cornell University).

In The Last Decade

Mehdi Mirza

5 papers receiving 8.8k citations

Hit Papers

Generative adversarial networks 2013 2026 2017 2021 2020 2013 2014 2.5k 5.0k 7.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Generative adversarial networks
    2020 8.1k citations Ian Goodfellow, Jean Pouget-Abadie et al. Communications of the ACM profile →
  2. Maxout Networks
    2013 380 citations Ian Goodfellow, David Warde-Farley et al. profile →
  3. An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
    2014 341 citations Ian Goodfellow, Mehdi Mirza et al. arXiv (Cornell University) profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mehdi Mirza Canada 5 3.9k 3.1k 735 729 719 5 9.2k
Sherjil Ozair United States 6 3.5k 0.9× 2.7k 0.9× 704 1.0× 699 1.0× 628 0.9× 7 8.5k
Jean Pouget-Abadie United States 6 3.3k 0.9× 2.5k 0.8× 698 0.9× 681 0.9× 574 0.8× 11 8.2k
Vinod Nair India 14 3.9k 1.0× 3.2k 1.0× 848 1.2× 674 0.9× 962 1.3× 23 9.8k
Xavier Glorot Canada 7 3.9k 1.0× 4.7k 1.5× 577 0.8× 682 0.9× 987 1.4× 7 10.3k
Soumith Chintala United States 12 5.2k 1.3× 3.9k 1.3× 675 0.9× 614 0.8× 749 1.0× 18 9.9k
P. M. Durai Raj Vincent India 28 2.7k 0.7× 4.0k 1.3× 486 0.7× 630 0.9× 914 1.3× 92 10.0k
Fuhui Long United States 20 2.4k 0.6× 3.0k 1.0× 746 1.0× 651 0.9× 652 0.9× 31 9.5k
Pierre-Antoine Manzagol Canada 7 3.1k 0.8× 3.7k 1.2× 591 0.8× 391 0.5× 1.2k 1.6× 9 8.1k
Chen Ding China 20 2.4k 0.6× 3.4k 1.1× 535 0.7× 612 0.8× 806 1.1× 125 9.0k

Countries citing papers authored by Mehdi Mirza

Since Specialization
Citations

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

Fields of papers citing papers by Mehdi Mirza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mehdi Mirza

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

All Works

5 of 5 papers shown
1.
Goodfellow, Ian, Jean Pouget-Abadie, Mehdi Mirza, et al.. (2020). Generative adversarial networks. Communications of the ACM. 63(11). 139–144. 8116 indexed citations breakdown →
2.
Kahou, Samira Ebrahimi, Xavier Bouthillier, Pascal Lamblin, et al.. (2015). EmoNets: Multimodal deep learning approaches for emotion recognition in video. Journal on Multimodal User Interfaces. 10(2). 99–111. 263 indexed citations
3.
Goodfellow, Ian, Mehdi Mirza, Xiao Da, Aaron Courville, & Yoshua Bengio. (2014). An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks. arXiv (Cornell University). 341 indexed citations breakdown →
4.
Goodfellow, Ian, Mehdi Mirza, Aaron Courville, & Yoshua Bengio. (2013). Multi-Prediction Deep Boltzmann Machines. Neural Information Processing Systems. 26. 548–556. 60 indexed citations
5.
Goodfellow, Ian, David Warde-Farley, Mehdi Mirza, Aaron Courville, & Yoshua Bengio. (2013). Maxout Networks. 380 indexed citations breakdown →

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

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2026