Johannes Lederer

About

Johannes Lederer is a scholar working on Statistics and Probability, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Johannes Lederer has authored 35 papers receiving a total of 385 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Statistics and Probability, 13 papers in Artificial Intelligence and 11 papers in Computational Mechanics. Recurrent topics in Johannes Lederer’s work include Statistical Methods and Inference (21 papers), Sparse and Compressive Sensing Techniques (11 papers) and Bayesian Methods and Mixture Models (5 papers). Johannes Lederer is often cited by papers focused on Statistical Methods and Inference (21 papers), Sparse and Compressive Sensing Techniques (11 papers) and Bayesian Methods and Mixture Models (5 papers). Johannes Lederer collaborates with scholars based in Germany, United States and Switzerland. Johannes Lederer's co-authors include Mohamed Hebiri, Sara van de Geer, Christian L. Müller, Yiyuan She, Florentina Bunea, Arnak S. Dalalyan, Irina Gaynanova, Yu Lu, David Gold and Wei Li and has published in prestigious journals such as Nucleic Acids Research, IEEE Transactions on Information Theory and Journal of Econometrics.

In The Last Decade

Co-authorship network of co-authors of Johannes Lederer i

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Fields of papers citing papers by Johannes Lederer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Johannes Lederer

Since Specialization

Citations

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

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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