Aurélien Garivier

3.2k citations
25 papers · 340 · h-index 9

Impact in

Papers in

Aurélien Garivier

22 papers receiving 325 citations

Peers

Aurélien Garivier
Comparison fields: 5 of 60
  • Management Science and Operations Research 147
  • Artificial Intelligence 224
  • Statistics and Probability 40
  • Computer Networks and Communications 76
  • Marketing 23
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Citations per year

Countries citing papers authored by Aurélien Garivier

Since Specialization
Citations

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

Fields of papers citing papers by Aurélien Garivier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Aurélien Garivier, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Aurélien Garivier Line = papers co-authored together Aurélien Garivier links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Parametric Bandits: The Generalized Linear Case
2010107
2 201187
3
Explore First, Exploit Next: The True Shape of Regret in Bandit Problems
201629
4 202020
5 200618
6 200812
7 201111
8 200911
9 201011
10 20216
11 20095
12 20085
13 20175
14 20083
15 20162
16 20092
17 20201
18
A Propp-Wilson perfect simulation scheme for processes with long memory
20111
19 20181
20 20191

About Aurélien Garivier

Aurélien Garivier is a scholar working on Artificial Intelligence, Management Science and Operations Research, Statistics and Probability, Signal Processing and Computer Networks and Communications, having authored 25 papers that have together received 340 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (8 papers), Machine Learning and Algorithms (6 papers), Algorithms and Data Compression (4 papers), Target Tracking and Data Fusion in Sensor Networks (4 papers), Bayesian Methods and Mixture Models (4 papers), Markov Chains and Monte Carlo Methods (3 papers), Blind Source Separation Techniques (3 papers) and Reinforcement Learning in Robotics (3 papers). The work is most often cited by research in Management Science and Operations Research (147 citations), Artificial Intelligence (224 citations), Statistics and Probability (40 citations), Computer Networks and Communications (76 citations) and Marketing (23 citations). Aurélien Garivier has collaborated with scholars based in France, Brazil and Sweden. Frequent co-authors include Sarah Filippi, Olivier Cappé, Éric Moulines, Csaba Szepesvári, Randal Douc, Jimmy Olsson, Pierre Ménard, Gilles Stoltz, Florencia Leonardi and Emilie Kaufmann. Their work appears in journals such as Journal of Statistical Planning and Inference, Reliability Engineering & System Safety, Stochastic Processes and their Applications, IEEE Transactions on Information Theory and Scandinavian Journal of Statistics.

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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