Paul Vicol

1000 total citations
8 papers, 22 citations indexed

About

Paul Vicol is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Paul Vicol has authored 8 papers receiving a total of 22 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 1 paper in Molecular Biology. Recurrent topics in Paul Vicol's work include Adversarial Robustness in Machine Learning (3 papers), Advanced Neural Network Applications (3 papers) and Neural Networks and Applications (2 papers). Paul Vicol is often cited by papers focused on Adversarial Robustness in Machine Learning (3 papers), Advanced Neural Network Applications (3 papers) and Neural Networks and Applications (2 papers). Paul Vicol collaborates with scholars based in Canada and United States. Paul Vicol's co-authors include Roger Grosse, Jimmy Ba, Li Gu, Kuan-Chieh Wang, Yeming Wen, James Lucas, Dustin Tran, David Duvenaud, Richard S. Zemel and Eleni Triantafillou and has published in prestigious journals such as The Fibonacci quarterly, arXiv (Cornell University) and International Conference on Machine Learning.

In The Last Decade

Paul Vicol

6 papers receiving 22 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Paul Vicol Canada	4	12	7	3	2	2	8	22
Cyril Zhang United States	3	10 0.8×	5 0.7×	3 1.0×	3 1.5×		6	16
Didrik Nielsen Denmark	3	14 1.2×	15 2.1×	2 0.7×	2 1.0×	1 0.5×	4	23
Pranav Shyam Switzerland	2	19 1.6×	13 1.9×	2 0.7×		2 1.0×	2	25
Xinyong Peng China	4	9 0.8×	5 0.7×	2 0.7×			12	21
Cem Anil United Kingdom	1	10 0.8×	4 0.6×	2 0.7×			2	12
Fan-Yun Sun Taiwan	2	8 0.7×	4 0.6×	3 1.0×	1 0.5×		6	18
Denis Teplyashin United Kingdom	2	15 1.3×	4 0.6×	2 0.7×			3	21
Belinda Z. Li United States	3	8 0.7×	4 0.6×	2 0.7×			3	9
Surbhi Goel United States	3	13 1.1×	8 1.1×		2 1.0×		8	18
Yunjie Pan China	2	7 0.6×	4 0.6×	4 1.3×			4	12

Countries citing papers authored by Paul Vicol

Since Specialization

Citations

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

Fields of papers citing papers by Paul Vicol

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paul Vicol

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

All Works

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8 of 8 papers shown

1.

Vicol, Paul, Luke Metz, & Jascha Sohl‐Dickstein. (2022). Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies (Extended Abstract). Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 5354–5358.

2.

Behrmann, Jens, Paul Vicol, Kuan-Chieh Wang, Roger Grosse, & Jörn-Henrik Jacobsen. (2019). On the Invertibility of Invertible Neural Networks. 1 indexed citations

3.

Wang, Kuan-Chieh, et al.. (2019). Out-of-distribution Detection in Few-shot Classification. 2 indexed citations

4.

Vicol, Paul, et al.. (2019). Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions. arXiv (Cornell University). 6 indexed citations

5.

Wang, Kuan-Chieh, Paul Vicol, James Lucas, et al.. (2018). Adversarial Distillation of Bayesian Neural Network Posteriors. International Conference on Machine Learning. 5190–5199. 3 indexed citations

6.

Wen, Yeming, Paul Vicol, Jimmy Ba, Dustin Tran, & Roger Grosse. (2018). Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. arXiv (Cornell University). 6 indexed citations

7.

Vicol, Paul, et al.. (2018). Reversible Recurrent Neural Networks. arXiv (Cornell University). 31. 9029–9040. 4 indexed citations

8.

Vicol, Paul, et al.. (2017). On Conway’s Subprime Function, A Covering of ℕ and an Unexpected Appearance of the Golden Ratio. The Fibonacci quarterly. 55(4). 327–331.

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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