Dániel Marx

9.0k total citations · 1 hit paper
147 papers, 2.9k citations indexed

About

Dániel Marx is a scholar working on Computational Theory and Mathematics, Computer Networks and Communications and Discrete Mathematics and Combinatorics. According to data from OpenAlex, Dániel Marx has authored 147 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 122 papers in Computational Theory and Mathematics, 55 papers in Computer Networks and Communications and 18 papers in Discrete Mathematics and Combinatorics. Recurrent topics in Dániel Marx's work include Advanced Graph Theory Research (117 papers), Complexity and Algorithms in Graphs (76 papers) and Constraint Satisfaction and Optimization (26 papers). Dániel Marx is often cited by papers focused on Advanced Graph Theory Research (117 papers), Complexity and Algorithms in Graphs (76 papers) and Constraint Satisfaction and Optimization (26 papers). Dániel Marx collaborates with scholars based in Hungary, Germany and Norway. Dániel Marx's co-authors include Martin Grohe, Daniel Lokshtanov, Saket Saurabh, Michał Pilipczuk, Marek Cygan, Marcin Pilipczuk, Fedor V. Fomin, Łukasz Kowalik, Ildikó Schlotter and Albert Atserias and has published in prestigious journals such as Communications of the ACM, Journal of the ACM and Journal of the Association for Information Systems.

In The Last Decade

Dániel Marx

136 papers receiving 2.8k 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.

Parameterized Algorithms

2015 745 citations Marek Cygan, Fedor V. Fomin et al. DIAL (Catholic University of Leuven) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dániel Marx Hungary	26	2.2k	1.1k	503	350	280	147	2.9k
Tomás Feder United States	23	1.5k 0.7×	850 0.8×	846 1.7×	314 0.9×	322 1.1×	87	2.8k
Saket Saurabh India	24	2.3k 1.1×	938 0.9×	329 0.7×	359 1.0×	86 0.3×	258	2.8k
Fedor V. Fomin Norway	32	3.7k 1.7×	1.7k 1.6×	657 1.3×	555 1.6×	111 0.4×	262	4.6k
Rolf Niedermeier Germany	31	2.5k 1.2×	1.1k 1.1×	863 1.7×	191 0.5×	145 0.5×	200	3.7k
Martin Grohe Germany	32	3.2k 1.5×	1.3k 1.2×	1.2k 2.5×	421 1.2×	459 1.6×	158	4.3k
Marek Karpiński Germany	26	1.6k 0.7×	917 0.9×	1.2k 2.3×	173 0.5×	167 0.6×	190	2.8k
Michael Saks United States	34	1.9k 0.9×	1.4k 1.4×	1.4k 2.7×	295 0.8×	94 0.3×	139	3.5k
Subhash Khot United States	26	2.3k 1.1×	897 0.9×	924 1.8×	173 0.5×	89 0.3×	116	2.9k
Rodney G. Downey New Zealand	21	3.3k 1.5×	829 0.8×	974 1.9×	221 0.6×	72 0.3×	129	3.9k
Hans L. Bodlaender Netherlands	38	4.5k 2.1×	1.8k 1.7×	964 1.9×	648 1.9×	186 0.7×	225	5.5k

Countries citing papers authored by Dániel Marx

Since Specialization

Citations

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

Fields of papers citing papers by Dániel Marx

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dániel Marx

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

All Works

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20 of 20 papers shown

1.

Marx, Dániel, et al.. (2024). Counting List Homomorphisms from Graphs of Bounded Treewidth: Tight Complexity Bounds. ACM Transactions on Algorithms. 20(2). 1–32. 1 indexed citations

2.

Cohen-Addad, Vincent, et al.. (2021). On the Computational Tractability of a Geographic Clustering Problem Arising in Redistricting. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 1 indexed citations

3.

Feldmann, Andreas Emil & Dániel Marx. (2018). The Parameterized Hardness of the k-Center Problem in Transportation\n Networks. arXiv (Cornell University). 2 indexed citations

4.

Berg, Mark de, et al.. (2018). SZTAKI Publication Repository (Hungarian Academy of Sciences). 11 indexed citations

5.

Bonnet, Édouard, et al.. (2018). Generalized Feedback Vertex Set Problems on Bounded-Treewidth Graphs: Chordality Is the Key to Single-Exponential Parameterized Algorithms. Middlesex University Research Repository (Middlesex University Of London).

6.

Havet, Frédéric, et al.. (2017). Coloring Graphs with Constraints on Connectivity. HAL (Le Centre pour la Communication Scientifique Directe). 4 indexed citations

7.

Marx, Dániel & Tillmann Miltzow. (2016). Peeling and Nibbling the Cactus: Subexponential-Time Algorithms for Counting Triangulations and Related Problems. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 51. 16. 2 indexed citations

8.

Cygan, Marek, Holger Dell, Daniel Lokshtanov, et al.. (2016). On Problems as Hard as CNF-SAT. ACM Transactions on Algorithms. 12(3). 1–24. 30 indexed citations

9.

Jansen, Bart M. P. & Dániel Marx. (2015). Characterizing the easy-to-find subgraphs from the viewpoint of polynomial-time algorithms, kernels, and Turing kernels. Symposium on Discrete Algorithms. 616–629. 8 indexed citations

10.

Cohen, David A., et al.. (2012). The Tractability of CSP Classes Defined by Forbidden Patterns. Journal of Artificial Intelligence Research. 45. 47–78. 10 indexed citations

11.

Bodlaender, Hans L., Rod Downey, Fedor V. Fomin, & Dániel Marx. (2012). The Multivariate Algorithmic Revolution and Beyond: essays dedicated to Michael R. Fellows on the occasion of His 60th birthday. DIAL (Catholic University of Leuven). 16 indexed citations

12.

Marx, Dániel. (2010). . Theory of Computing. 6(1). 85–112. 63 indexed citations

13.

Marx, Dániel, et al.. (2009). Argelia, crónica de una reelección anunciada. 17.

14.

Marx, Dániel. (2009). Approximating fractional hypertree width. Symposium on Discrete Algorithms. 902–911. 8 indexed citations

15.

Marx, Dániel, et al.. (2009). Media Coverage of Online Social Network Privacy Issues in Germany: A Thematic Analysis. Journal of the Association for Information Systems. 342. 23 indexed citations

16.

Grohe, Martin & Dániel Marx. (2008). On tree width, bramble size, and expansion. Journal of Combinatorial Theory Series B. 99(1). 218–228. 34 indexed citations

17.

Marx, Dániel. (2007). Can you beat treewidth?. 169–179. 23 indexed citations

18.

Marx, Dániel. (2004). GRAPH COLOURING PROBLEMS AND THEIR APPLICATIONS IN SCHEDULING. 48. 11–16. 71 indexed citations

19.

Marx, Dániel. (2004). Parameterized complexity of constraint satisfaction problems. 139–149. 3 indexed citations

20.

Marx, Dániel, et al.. (1994). Sex determination of bovine fetuses by ultrasonography. Tierärztliche Umschau. 49(8). 484–486. 3 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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