Mario Geiger

21 papers and 1.2k indexed citations i.

About

Mario Geiger is a scholar working on Artificial Intelligence, Materials Chemistry and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mario Geiger has authored 21 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 5 papers in Materials Chemistry and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mario Geiger’s work include Neural Networks and Applications (7 papers), Stochastic Gradient Optimization Techniques (4 papers) and Machine Learning in Materials Science (3 papers). Mario Geiger is often cited by papers focused on Neural Networks and Applications (7 papers), Stochastic Gradient Optimization Techniques (4 papers) and Machine Learning in Materials Science (3 papers). Mario Geiger collaborates with scholars based in Switzerland, France and United States. Mario Geiger's co-authors include Tess Smidt, Simon Batzner, Lixin Sun, Mordechai Kornbluth, Albert Musaelian, Boris Kozinsky, Jonathan P. Mailoa, Nicola Molinari, Matthieu Wyart and Stefano Spigler and has published in prestigious journals such as New England Journal of Medicine, Nature Communications and Physics Reports.

In The Last Decade

Co-authorship network of co-authors of Mario Geiger i

Fields of papers citing papers by Mario Geiger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Mario Geiger

Since Specialization
Citations

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