Karol Kurach

1.3k total citations
8 papers, 181 citations indexed

About

Karol Kurach is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Karol Kurach has authored 8 papers receiving a total of 181 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Signal Processing. Recurrent topics in Karol Kurach's work include Neural Networks and Applications (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Topic Modeling (2 papers). Karol Kurach is often cited by papers focused on Neural Networks and Applications (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Topic Modeling (2 papers). Karol Kurach collaborates with scholars based in United States, Switzerland and Poland. Karol Kurach's co-authors include Miklós Bálint, Tobias Kaufmann, Lukács László, Peter Young, Andrew Tomkins, Anjuli Kannan, Vivek Ramavajjala, Greg S. Corrado, Sylvain Gelly and Sjoerd van Steenkiste and has published in prestigious journals such as SHILAP Revista de lepidopterología, Neural Networks and arXiv (Cornell University).

In The Last Decade

Karol Kurach

8 papers receiving 173 citations

Peers

Karol Kurach
Vivek Ramavajjala United States
Dominik Heckmann Germany
Samuel Jenkins United States
Thomas Rodriguez United States
Ellen Jiang United States
Kang Min Yoo South Korea
Çağatay Demiralp United States
Anitha S. Pillai India
Peter Zimmermann United States
Hengyi Cai China
Vivek Ramavajjala United States
Karol Kurach
Citations per year, relative to Karol Kurach Karol Kurach (= 1×) peers Vivek Ramavajjala

Countries citing papers authored by Karol Kurach

Since Specialization
Citations

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

Fields of papers citing papers by Karol Kurach

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Karol Kurach

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

All Works

8 of 8 papers shown
1.
Steenkiste, Sjoerd van, Karol Kurach, Jürgen Schmidhuber, & Sylvain Gelly. (2020). Investigating object compositionality in Generative Adversarial Networks. Neural Networks. 130. 309–325. 9 indexed citations
2.
Unterthiner, Thomas, Sjoerd van Steenkiste, Karol Kurach, et al.. (2019). FVD: A new Metric for Video Generation. International Conference on Learning Representations. 27 indexed citations
3.
Steenkiste, Sjoerd van, Karol Kurach, & Sylvain Gelly. (2018). A Case for Object Compositionality in Deep Generative Models of Images. 2 indexed citations
4.
Kurach, Karol & Krzysztof Pawłowski. (2016). Predicting Dangerous Seismic Activity with Recurrent Neural Networks. SHILAP Revista de lepidopterología. 8. 239–243. 9 indexed citations
5.
Kannan, Anjuli, Karol Kurach, Tobias Kaufmann, et al.. (2016). Smart Reply. 955–964. 114 indexed citations
6.
Kurach, Karol, Marcin Andrychowicz, & Ilya Sutskever. (2015). Neural Random-Access Machines. arXiv (Cornell University). 2016. 4 indexed citations
7.
Pawłowski, Krzysztof, et al.. (2014). Coalition structure generation with the graphics processing unit. Adaptive Agents and Multi-Agents Systems. 293–300. 5 indexed citations
8.
Zaremba, Wojciech, Karol Kurach, & Rob Fergus. (2014). Learning to Discover Efficient Mathematical Identities. arXiv (Cornell University). 27. 1278–1286. 11 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