Countries where authors publish in Inverse Problems
Since Specialization
Citations
This map shows the geographic impact of research published in Inverse Problems. 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 papers published in Inverse Problems with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Inverse Problems more than expected).
This network shows the impact of papers published in Inverse Problems. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Inverse Problems.
About Inverse Problems
The 4.4k papers published in Inverse Problems in the last decades have received a total of 120.4k indexed citations . Papers published in Inverse Problems usually cover Mathematical Physics (2.4k papers), Applied Mathematics (489 papers), Computational Theory and Mathematics (774 papers), Geophysics (521 papers) and Statistical and Nonlinear Physics (455 papers) specifically the topics of Numerical methods in inverse problems (2.3k papers), Microwave Imaging and Scattering Analysis (902 papers), Advanced Mathematical Modeling in Engineering (598 papers), Sparse and Compressive Sensing Techniques (418 papers), Geophysical Methods and Applications (394 papers), Electrical and Bioimpedance Tomography (379 papers), Ultrasonics and Acoustic Wave Propagation (346 papers) and Medical Imaging Techniques and Applications (335 papers). The most active scholars publishing in Inverse Problems are Simon Arridge, Charles L. Byrne, Andreas Kirsch, Masahiro Yamamoto, David Colton, Hong‐Kun Xu, Liliana Borcea, Philipp Hartl, Richard Bamler and Emmanuel J. Candès.
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.