Marek Krčál
Impact in
- Signal Processing top 10%
- Advanced Malware Detection Techniques
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- Topological and Geometric Data Analysis
Papers in
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- Topological and Geometric Data Analysis 7
- Polynomial and algebraic computation 2
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- Homotopy and Cohomology in Algebraic Topology 6
- Co-authors
- Jiřı́ Sgall (1 shared paper)Jiřı́ Matoušek (5 shared papers)Uli Wagner (4 shared papers)Francis Sergeraert (2 shared papers)Stephan Kreutzer (1 shared paper)Ken‐ichi Kawarabayashi (1 shared paper)Daniel Král͏̌ (1 shared paper)Martin Holeňa (1 shared paper)
- Journals
- Journal of the ACM (2 papers)Discrete & Computational Geometry (2 papers)Algorithmica (1 paper)Foundations of Computational Mathematics (1 paper)SIAM Journal on Computing (1 paper)
- Partner nations
- CzechiaAustriaSwitzerland
In The Last Decade
Marek Krčál
12 papers receiving 143 citations
Peers
Comparison fields: 5 of 26
- Signal Processing 61
- Computational Theory and Mathematics 62
- Geometry and Topology 31
- Mathematical Physics 30
- Computer Networks and Communications 67
Countries citing papers authored by Marek Krčál
This map shows the geographic impact of Marek Krčál'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 Marek Krčál with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marek Krčál more than expected).
Fields of papers citing papers by Marek Krčál
This network shows the impact of papers produced by Marek Krčál. 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 Marek Krčál. The network helps show where Marek Krčál may publish in the future.
Co-authors
The 8 scholars most cited alongside Marek Krčál, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Deep Convolutional Malware Classifiers Can Learn from Raw Executables and Labels Only | 2018 | 63 |
| 2 | 2012 | 33 | |
| 3 | 2013 | 11 | |
| 4 | 2014 | 10 | |
| 5 | 2014 | 10 | |
| 6 | 2013 | 9 | |
| 7 | Packing directed cycles through a specified vertex set | 2013 | 5 |
| 8 | 2015 | 4 | |
| 9 | 2013 | 3 | |
| 10 | Two Semi-supervised Approaches to Malware Detection with Neural Networks. | 2020 | 2 |
| 11 | 2016 | 1 | |
| 12 | Computational Homotopy Theory | 2013 | 1 |
About Marek Krčál
Marek Krčál is a scholar working on Computational Theory and Mathematics, Mathematical Physics, Geometry and Topology, Computer Networks and Communications and Signal Processing, having authored 12 papers that have together received 152 indexed citations. Recurring topics across this work include Topological and Geometric Data Analysis (7 papers), Homotopy and Cohomology in Algebraic Topology (6 papers), Advanced Topology and Set Theory (3 papers), Polynomial and algebraic computation (2 papers), Anomaly Detection Techniques and Applications (2 papers), Advanced Malware Detection Techniques (2 papers), Network Security and Intrusion Detection (2 papers) and Advanced Topics in Algebra (1 paper). The work is most often cited by research in Signal Processing (61 citations), Computational Theory and Mathematics (62 citations), Geometry and Topology (31 citations), Mathematical Physics (30 citations) and Computer Networks and Communications (67 citations). Marek Krčál has collaborated with scholars based in Czechia, Austria and Switzerland. Frequent co-authors include Jiřı́ Sgall, Jiřı́ Matoušek, Uli Wagner, Francis Sergeraert, Stephan Kreutzer, Ken‐ichi Kawarabayashi, Daniel Král͏̌ and Martin Holeňa. Their work appears in journals such as Journal of the ACM, Discrete & Computational Geometry, Algorithmica, Foundations of Computational Mathematics and SIAM Journal on Computing.
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.