John Salvatier

About

John Salvatier is a scholar working on Artificial Intelligence, Clinical Psychology and Modeling and Simulation. According to data from OpenAlex, John Salvatier has authored 3 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 1 paper in Clinical Psychology and 1 paper in Modeling and Simulation. Recurrent topics in John Salvatier’s work include Computational Physics and Python Applications (2 papers), COVID-19 Pandemic Impacts (1 paper) and Gaussian Processes and Bayesian Inference (1 paper). John Salvatier is often cited by papers focused on Computational Physics and Python Applications (2 papers), COVID-19 Pandemic Impacts (1 paper) and Gaussian Processes and Bayesian Inference (1 paper). John Salvatier collaborates with scholars based in United States, United Kingdom and Australia. John Salvatier's co-authors include Christopher Fonnesbeck, Thomas V. Wiecki, Yee Whye Teh, Anna B. Stephenson, Mrinank Sharma, Jan Brauner, Alexander John Norman, Joshua Teperowski Monrad, Sören Mindermann and David Johnston and has published in prestigious journals such as Science, PeerJ Computer Science and Astrophysics Source Code Library.

In The Last Decade

Co-authorship network of co-authors of John Salvatier i

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Fields of papers citing papers by John Salvatier

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by John Salvatier

Since Specialization

Citations

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