Martin Jaggi

69 papers and 1.4k indexed citations i.

About

Martin Jaggi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Mechanics. According to data from OpenAlex, Martin Jaggi has authored 69 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Artificial Intelligence, 16 papers in Computer Vision and Pattern Recognition and 14 papers in Computational Mechanics. Recurrent topics in Martin Jaggi’s work include Stochastic Gradient Optimization Techniques (22 papers), Sparse and Compressive Sensing Techniques (14 papers) and Topic Modeling (13 papers). Martin Jaggi is often cited by papers focused on Stochastic Gradient Optimization Techniques (22 papers), Sparse and Compressive Sensing Techniques (14 papers) and Topic Modeling (13 papers). Martin Jaggi collaborates with scholars based in Switzerland, United States and Germany. Martin Jaggi's co-authors include Sebastian U. Stich, Aurélien Lucchi, Jean-Baptiste Cordonnier, Claudiu Musat, Chenxin Ma, Martin Takáč, Valéria De Luca, Virginia Smith, Michael I. Jordan and Thomas Hofmann and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Machine Learning Research and SIAM Journal on Optimization.

In The Last Decade

Co-authorship network of co-authors of Martin Jaggi i

Fields of papers citing papers by Martin Jaggi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Martin Jaggi

Since Specialization
Citations

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