Mohamed Hebiri

55 total papers · 669 total citations
13 papers, 242 citations indexed

About

Mohamed Hebiri is a scholar working on Artificial Intelligence, Statistics and Probability and Computational Mechanics. According to data from OpenAlex, Mohamed Hebiri has authored 13 papers receiving a total of 242 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Statistics and Probability and 4 papers in Computational Mechanics. Recurrent topics in Mohamed Hebiri's work include Statistical Methods and Inference (7 papers), Machine Learning and Algorithms (4 papers) and Sparse and Compressive Sensing Techniques (4 papers). Mohamed Hebiri is often cited by papers focused on Statistical Methods and Inference (7 papers), Machine Learning and Algorithms (4 papers) and Sparse and Compressive Sensing Techniques (4 papers). Mohamed Hebiri collaborates with scholars based in France, Switzerland and Belgium. Mohamed Hebiri's co-authors include Johannes Lederer, Sara van de Geer, Arnak S. Dalalyan, Pierre Alquier, Massimiliano Pontil, Cristina Butucea, Tomoyuki Morimae, Luca Oneto and Xavier Siebert and has published in prestigious journals such as IEEE Transactions on Information Theory, Physical Review A and Machine Learning.

In The Last Decade

Mohamed Hebiri

12 papers receiving 233 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Mohamed Hebiri	96	70	65	30	21	13	242
Klaus Frick	110 1.1×	43 0.6×	74 1.1×	31 1.0×	37 1.8×	21	316
Yiqiao Zhong	98 1.0×	78 1.1×	81 1.2×	15 0.5×	9 0.4×	14	288
Tingni Sun	201 2.1×	91 1.3×	35 0.5×	53 1.8×	17 0.8×	9	279
Vincent Q. Vu	70 0.7×	67 1.0×	61 0.9×	27 0.9×	6 0.3×	13	268
Artin Armagan	200 2.1×	111 1.6×	31 0.5×	54 1.8×	12 0.6×	9	320
Stanislav Minsker	141 1.5×	111 1.6×	57 0.9×	10 0.3×	15 0.7×	21	276
P. Hall	166 1.7×	75 1.1×	11 0.2×	33 1.1×	25 1.2×	17	319
Arne Kovac	85 0.9×	43 0.6×	48 0.7×	23 0.8×	30 1.4×	8	261
Rui M. Castro	19 0.2×	74 1.1×	76 1.2×	19 0.6×	16 0.8×	13	233
Changbo Zhu	57 0.6×	62 0.9×	115 1.8×	9 0.3×	7 0.3×	14	285

Countries citing papers authored by Mohamed Hebiri

Since Specialization

Citations

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

Fields of papers citing papers by Mohamed Hebiri

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohamed Hebiri

This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed Hebiri. A scholar is included among the top collaborators of Mohamed Hebiri 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 Mohamed Hebiri. Mohamed Hebiri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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