Patrick Rebeschini

453 total citations
14 papers, 178 citations indexed

About

Patrick Rebeschini is a scholar working on Statistics and Probability, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Patrick Rebeschini has authored 14 papers receiving a total of 178 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Statistics and Probability, 7 papers in Artificial Intelligence and 5 papers in Computational Mechanics. Recurrent topics in Patrick Rebeschini's work include Markov Chains and Monte Carlo Methods (6 papers), Sparse and Compressive Sensing Techniques (5 papers) and Stochastic Gradient Optimization Techniques (5 papers). Patrick Rebeschini is often cited by papers focused on Markov Chains and Monte Carlo Methods (6 papers), Sparse and Compressive Sensing Techniques (5 papers) and Stochastic Gradient Optimization 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, Lorenzo Rosasco, Amin Karbasi and Fan Wu and has published in prestigious journals such as The Annals of Applied Probability, Electronic Journal of Probability and Information and Inference A Journal of the IMA.

In The Last Decade

Patrick Rebeschini

14 papers receiving 173 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Patrick Rebeschini United Kingdom 5 114 32 29 29 26 14 178
Andrey Gorshenin Russia 9 80 0.7× 33 1.0× 36 1.2× 48 1.7× 29 1.1× 54 250
Radu Herbei United States 10 142 1.2× 68 2.1× 36 1.2× 35 1.2× 38 1.5× 24 327
François Desbouvries France 10 186 1.6× 11 0.3× 19 0.7× 10 0.3× 7 0.3× 41 284
Bernard Garel France 11 96 0.8× 127 4.0× 26 0.9× 41 1.4× 30 1.2× 23 270
Daniel Sanz-Alonso United States 8 111 1.0× 72 2.3× 44 1.5× 23 0.8× 8 0.3× 27 227
Alessandra Luati Italy 8 28 0.2× 36 1.1× 9 0.3× 24 0.8× 25 1.0× 36 234
Isao Shoji Japan 9 36 0.3× 47 1.5× 7 0.2× 49 1.7× 18 0.7× 30 364
Granville Tunnicliffe‐Wilson Ghana 3 72 0.6× 26 0.8× 8 0.3× 15 0.5× 23 0.9× 4 339
Bruno Betrò Italy 9 84 0.7× 70 2.2× 9 0.3× 14 0.5× 38 1.5× 22 202
Jean‐François Coeurjolly France 11 36 0.3× 55 1.7× 6 0.2× 33 1.1× 25 1.0× 37 480

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).

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.

Co-authorship network of co-authors of Patrick Rebeschini

This figure shows the co-authorship network connecting the top 25 collaborators of Patrick Rebeschini. A scholar is included among the top collaborators of Patrick Rebeschini based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Patrick Rebeschini. Patrick Rebeschini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Kanade, Varun, et al.. (2023). The statistical complexity of early-stopped mirror descent. Information and Inference A Journal of the IMA. 12(4). 3010–3041. 1 indexed citations
2.
Wu, Fan & Patrick Rebeschini. (2022). Nearly minimax-optimal rates for noisy sparse phase retrieval via early-stopped mirror descent. Information and Inference A Journal of the IMA. 12(2). 633–713. 1 indexed citations
3.
Rebeschini, Patrick, et al.. (2020). Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent. Oxford University Research Archive (ORA) (University of Oxford). 21(34). 1–44. 7 indexed citations
4.
Rebeschini, Patrick, et al.. (2020). Decentralised Learning with Random Features and Distributed Gradient Descent. arXiv (Cornell University). 1. 8105–8115. 4 indexed citations
5.
Kanade, Varun, et al.. (2020). The Statistical Complexity of Early-Stopped Mirror Descent. arXiv (Cornell University). 33. 253–264. 1 indexed citations
6.
Rebeschini, Patrick, et al.. (2019). Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up. arXiv (Cornell University). 32. 1214–1225. 2 indexed citations
7.
Kanade, Varun, et al.. (2019). Implicit Regularization for Optimal Sparse Recovery. arXiv (Cornell University). 32. 2968–2979. 7 indexed citations
8.
Kanade, Varun, et al.. (2018). Decentralized Cooperative Stochastic Bandits. arXiv (Cornell University). 32. 4529–4540. 25 indexed citations
9.
Rebeschini, Patrick & Sekhar Tatikonda. (2016). A New Approach to Laplacian Solvers and Flow Problems. arXiv (Cornell University). 20(36). 1–37. 3 indexed citations
10.
Rebeschini, Patrick & Ramon van Handel. (2016). COMPARISON THEOREMS FOR GIBBS MEASURES∗. 1 indexed citations
11.
Rebeschini, Patrick & Amin Karbasi. (2015). Fast Mixing for Discrete Point Processes. Conference on Learning Theory. 1480–1500. 2 indexed citations
12.
Rebeschini, Patrick & Ramon van Handel. (2015). Phase transitions in nonlinear filtering. Electronic Journal of Probability. 20(none). 3 indexed citations
13.
Rebeschini, Patrick & Ramon van Handel. (2015). Can local particle filters beat the curse of dimensionality?. The Annals of Applied Probability. 25(5). 118 indexed citations
14.
Rebeschini, Patrick. (2014). Nonlinear Filtering in High Dimension. 3 indexed citations

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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