Sherjil Ozair

22.1k total citations · 2 hit papers
7 papers, 8.5k citations indexed

About

Sherjil Ozair is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Sherjil Ozair has authored 7 papers receiving a total of 8.5k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 1 paper in Computational Theory and Mathematics. Recurrent topics in Sherjil Ozair's work include Bayesian Modeling and Causal Inference (3 papers), Generative Adversarial Networks and Image Synthesis (3 papers) and Image and Signal Denoising Methods (1 paper). Sherjil Ozair is often cited by papers focused on Bayesian Modeling and Causal Inference (3 papers), Generative Adversarial Networks and Image Synthesis (3 papers) and Image and Signal Denoising Methods (1 paper). Sherjil Ozair collaborates with scholars based in United States, Canada and India. Sherjil Ozair's co-authors include Yoshua Bengio, Aaron Courville, Mehdi Mirza, Ian Goodfellow, Bing Xu, Jean Pouget-Abadie, David Warde-Farley, Aristide Baratin, Devon Hjelm and Mohamed Ishmael Belghazi and has published in prestigious journals such as Communications of the ACM, ACM SIGPLAN Notices and arXiv (Cornell University).

In The Last Decade

Sherjil Ozair

7 papers receiving 8.2k citations

Hit Papers

align trajectories

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.

Generative adversarial networks

2020 8.1k citations Ian Goodfellow, Jean Pouget-Abadie et al. Communications of the ACM profile →
Mutual Information Neural Estimation.

2018 302 citations Mohamed Ishmael Belghazi, Aristide Baratin et al. International Conference on Machine Learning profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sherjil Ozair United States	6	3.5k	2.7k	704	699	628	7	8.5k
Jean Pouget-Abadie United States	6	3.3k 1.0×	2.5k 0.9×	698 1.0×	681 1.0×	574 0.9×	11	8.2k
Mehdi Mirza Canada	5	3.9k 1.1×	3.1k 1.1×	735 1.0×	729 1.0×	719 1.1×	5	9.2k
Vinod Nair India	14	3.9k 1.1×	3.2k 1.2×	848 1.2×	674 1.0×	962 1.5×	23	9.8k
P. M. Durai Raj Vincent India	28	2.7k 0.8×	4.0k 1.5×	486 0.7×	630 0.9×	914 1.5×	92	10.0k
Soumith Chintala United States	12	5.2k 1.5×	3.9k 1.4×	675 1.0×	614 0.9×	749 1.2×	18	9.9k
Xavier Glorot Canada	7	3.9k 1.1×	4.7k 1.7×	577 0.8×	682 1.0×	987 1.6×	7	10.3k
Chen Ding China	20	2.4k 0.7×	3.4k 1.2×	535 0.8×	612 0.9×	806 1.3×	125	9.0k
Christian Igel Denmark	36	2.5k 0.7×	3.6k 1.3×	736 1.0×	634 0.9×	519 0.8×	162	7.7k
Pierre-Antoine Manzagol Canada	7	3.1k 0.9×	3.7k 1.4×	591 0.8×	391 0.6×	1.2k 1.8×	9	8.1k

Countries citing papers authored by Sherjil Ozair

Since Specialization

Citations

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

Fields of papers citing papers by Sherjil Ozair

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sherjil Ozair

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

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 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.

Lamb, Alex, Sherjil Ozair, Vikas Verma, & David Ha. (2020). SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks. 17. 952–961. 5 indexed citations

3.

Poole, Ben, Sherjil Ozair, Aäron van den Oord, Alexander A. Alemi, & George Tucker. (2019). On Variational Bounds of Mutual Information. arXiv (Cornell University). 5171–5180. 46 indexed citations

4.

Belghazi, Mohamed Ishmael, Aristide Baratin, Sherjil Ozair, et al.. (2018). Mutual Information Neural Estimation.. International Conference on Machine Learning. 531–540. 302 indexed citations breakdown →

5.

Nori, Aditya V., et al.. (2015). Efficient synthesis of probabilistic programs. 208–217. 15 indexed citations

6.

Nori, Aditya V., et al.. (2015). Efficient synthesis of probabilistic programs. ACM SIGPLAN Notices. 50(6). 208–217. 8 indexed citations

7.

Ozair, Sherjil, Li Yao, & Yoshua Bengio. (2013). Multimodal Transitions for Generative Stochastic Networks. International Conference on Learning Representations. 4 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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