J. J. Swetits

645 citations
41 papers · 458 indexed · h-index 11
Topics
Approximation Theory and Sequence Spaces (20 papers)Mathematical Approximation and Integration (14 papers)Mathematical functions and polynomials (13 papers)

In The Last Decade

J. J. Swetits

39 papers receiving 389 citations

Peers

J. J. Swetits
Comparison fields: 5 of 53
  • Numerical Analysis 226
  • Statistics and Probability 161
  • Computational Theory and Mathematics 154
  • Applied Mathematics 153
  • Control and Systems Engineering 85
Replace H. L. Loeb with:
H. L. Loeb United States
Zvi Ziegler Israel
John A. Roulier United States
D. Kershaw United Kingdom
V. Maiorov Israel
Leszek Plaskota Poland
L. A. Karlovitz United States
Alan Feldstein United States
H. L. Garabedian United States
Kurt Jetter Germany
J. J. Swetits relative to H. L. Loeb United States H. L. Loeb's profile →
Citations per field
00.5×10×14×
H. L. Loeb · 1×
Citations per year

Countries citing papers authored by J. J. Swetits

Since Specialization
Citations

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

Fields of papers citing papers by J. J. Swetits

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. J. Swetits

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 5
3 1
4 8
5 3
6 1
7 3
8 11
9 15
10 2
11 7
12 4
13 3
14 6
15 5
16 5
17 1
18 29
19 2
20 26

About J. J. Swetits

J. J. Swetits is a scholar working on Numerical Analysis, Applied Mathematics and Statistics and Probability, having authored 41 papers that have together received 458 indexed citations. Recurring topics across this work include Approximation Theory and Sequence Spaces (20 papers), Mathematical Approximation and Integration (14 papers) and Mathematical functions and polynomials (13 papers). The work is most often cited by research in Numerical Analysis (226 citations), Statistics and Probability (161 citations) and Applied Mathematics (153 citations). J. J. Swetits has collaborated with scholars based in United States, Hungary and Germany. Frequent co-authors include Wu Li, Philip W. Smith, Charles A. Micchelli, J. D. Ward, J. P. King, Frank Deutsch, Yuesheng Xu, Darrell Schmidt, Manfred Müller and András Kroó. Their work appears in journals such as SIAM Journal on Scientific Computing, American Mathematical Monthly and SIAM Journal on Optimization.

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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