Patrick Rebeschini

15 papers and 138 indexed citations i.

About

Patrick Rebeschini is a scholar working on Artificial Intelligence, Statistics and Probability and Computational Mechanics. According to data from OpenAlex, Patrick Rebeschini has authored 15 papers receiving a total of 138 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Statistics and Probability and 5 papers in Computational Mechanics. Recurrent topics in Patrick Rebeschini’s work include Stochastic Gradient Optimization Techniques (7 papers), Markov Chains and Monte Carlo Methods (5 papers) and Sparse and Compressive Sensing Techniques (5 papers). Patrick Rebeschini is often cited by papers focused on Stochastic Gradient Optimization Techniques (7 papers), Markov Chains and Monte Carlo Methods (5 papers) and Sparse and Compressive Sensing Techniques (5 papers). Patrick Rebeschini collaborates with scholars based in United Kingdom, United States and Switzerland. Patrick Rebeschini's co-authors include Ramon van Handel, Varun Kanade, Sekhar Tatikonda, Amin Karbasi, Fan Wu and Lorenzo Rosasco and has published in prestigious journals such as Journal of Statistical Physics, The Annals of Applied Probability and IEEE Transactions on Control of Network Systems.

In The Last Decade

Co-authorship network of co-authors of Patrick Rebeschini i

Fields of papers citing papers by Patrick Rebeschini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Patrick Rebeschini

Since Specialization
Citations

This map shows the geographic impact of Patrick Rebeschini'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 Patrick Rebeschini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Rebeschini 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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2025