This map shows the geographic impact of Walter Krämer'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 Walter Krämer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Walter Krämer more than expected).
This network shows the impact of papers produced by Walter Krämer. 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 Walter Krämer. The network helps show where Walter Krämer may publish in the future.
Co-authorship network of co-authors of Walter Krämer
This figure shows the co-authorship network connecting the top 25 collaborators of Walter Krämer.
A scholar is included among the top collaborators of Walter Krämer 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 Walter Krämer. Walter Krämer 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
1.
Krämer, Walter. (2020). Constructive Error Analysis. Zenodo (CERN European Organization for Nuclear Research).
Krämer, Walter, et al.. (2011). Efficient Parallel Solvers for Large Dense Systems of Linear Interval Equations. Reliable Computing. 15. 193–206.5 indexed citations
Krämer, Walter. (1987). Inverse Standardfunktionen für reelle und komplexe Intervallargumente mit a priori Fehlerabschätzungen für beliebige Datenformate. Medical Entomology and Zoology.2 indexed citations
20.
Bohlender, Gerd, Hans‐Joachim Böhm, E. Kaucher, et al.. (1983). MATRIX PASCAL. 311–384.1 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.