G. Reents

18 total papers · 530 total citations
16 papers, 230 citations indexed

About

G. Reents is a scholar working on Mathematical Physics, Artificial Intelligence and Statistical and Nonlinear Physics. According to data from OpenAlex, G. Reents has authored 16 papers receiving a total of 230 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Mathematical Physics, 5 papers in Artificial Intelligence and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in G. Reents's work include Neural Networks and Applications (3 papers), Advanced Algebra and Geometry (3 papers) and Advanced MRI Techniques and Applications (2 papers). G. Reents is often cited by papers focused on Neural Networks and Applications (3 papers), Advanced Algebra and Geometry (3 papers) and Advanced MRI Techniques and Applications (2 papers). G. Reents collaborates with scholars based in Germany, United States and Israel. G. Reents's co-authors include Wolfgang Kinzel, Robert Urbanczik, Ido Kanter, A. Englert, M. Zigzag, Wolfgang R. Bauer, Christian H. Ziener, Thomas Kampf, Heinz‐Peter Schlemmer and Michael Biehl and has published in prestigious journals such as Physical Review Letters, Communications in Mathematical Physics and Physica A Statistical Mechanics and its Applications.

In The Last Decade

G. Reents

16 papers receiving 223 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
G. Reents	69	65	57	54	42	16	230
Martin Köhler	71 1.0×	48 0.7×	10 0.2×	49 0.9×	76 1.8×	18	315
Jiaxi Ying	15 0.2×	18 0.3×	80 1.4×	50 0.9×	40 1.0×	27	270
Julien Salomon	38 0.6×	13 0.2×	13 0.2×	26 0.5×	18 0.4×	21	289
Gorka Muñoz-Gil	81 1.2×	6 0.1×	16 0.3×	30 0.6×	11 0.3×	18	228
Julian Kates‐Harbeck	18 0.3×	25 0.4×	13 0.2×	55 1.0×	135 3.2×	10	296
John Maidens	9 0.1×	24 0.4×	91 1.6×	26 0.5×	14 0.3×	22	331
Jackson R. Mayo	25 0.4×	32 0.5×	15 0.3×	24 0.4×	5 0.1×	21	302
Brendan Ames	33 0.5×	14 0.2×	6 0.1×	63 1.2×	13 0.3×	12	219
Thomas Schürmann	94 1.4×	26 0.4×	4 0.1×	116 2.1×	15 0.4×	10	314
Yixuan Li	144 2.1×	43 0.7×	3 0.1×	70 1.3×	56 1.3×	20	255

Countries citing papers authored by G. Reents

Since Specialization

Citations

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

Fields of papers citing papers by G. Reents

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Reents

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

All Works

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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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