L. Personnaz

4.6k total citations · 1 hit paper
44 papers, 2.5k citations indexed

About

L. Personnaz is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, L. Personnaz has authored 44 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Artificial Intelligence, 19 papers in Control and Systems Engineering and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in L. Personnaz's work include Neural Networks and Applications (34 papers), Control Systems and Identification (13 papers) and Fault Detection and Control Systems (11 papers). L. Personnaz is often cited by papers focused on Neural Networks and Applications (34 papers), Control Systems and Identification (13 papers) and Fault Detection and Control Systems (11 papers). L. Personnaz collaborates with scholars based in France and Germany. L. Personnaz's co-authors include Isabelle Rivals, Gérard Dreyfus, Marie‐Claude Potier, Lieng Taing, Isabelle Guyon, Isabelle Guyon, S. Knerr, P. Roussel-Ragot, Yacine Oussar and Sylvie Marcos and has published in prestigious journals such as Bioinformatics, Journal of Neurochemistry and The American Journal of Human Genetics.

In The Last Decade

L. Personnaz

41 papers receiving 2.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Enrichment or depletion of a GO category within a class of genes: which test?

2006 496 citations Isabelle Rivals, L. Personnaz et al. Bioinformatics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
L. Personnaz France	21	1.1k	553	455	272	250	44	2.5k
Fernando J. Pineda United States	18	761 0.7×	826 1.5×	196 0.4×	186 0.7×	115 0.5×	40	2.2k
Ulisses Braga-Neto United States	33	636 0.6×	1.3k 2.4×	305 0.7×	140 0.5×	387 1.5×	135	3.4k
Tadeusz Wilusz Poland	17	740 0.7×	838 1.5×	325 0.7×	400 1.5×	307 1.2×	61	3.1k
Min Xiao China	33	1.0k 1.0×	379 0.7×	344 0.8×	397 1.5×	162 0.6×	291	4.0k
Sen Zhang China	29	1.0k 0.9×	381 0.7×	304 0.7×	349 1.3×	245 1.0×	218	2.7k
Ping Ma China	31	569 0.5×	794 1.4×	490 1.1×	324 1.2×	133 0.5×	204	3.3k
Mahesan Niranjan United Kingdom	26	1.4k 1.3×	365 0.7×	385 0.8×	261 1.0×	496 2.0×	206	2.8k
Jorge Gonçalves Luxembourg	26	246 0.2×	789 1.4×	586 1.3×	170 0.6×	75 0.3×	127	2.8k
David M. Auslander United States	33	196 0.2×	1.0k 1.8×	882 1.9×	508 1.9×	59 0.2×	172	3.5k
Yves Chauvin United States	16	801 0.7×	1.5k 2.8×	72 0.2×	95 0.3×	264 1.1×	26	3.1k

Countries citing papers authored by L. Personnaz

Since Specialization

Citations

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

Fields of papers citing papers by L. Personnaz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of L. Personnaz

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Ait‐Yahya, Emilie, Julie Aubert, Luce Dauphinot, et al.. (2007). Classification of Human Chromosome 21 Gene-Expression Variations in Down Syndrome: Impact on Disease Phenotypes. The American Journal of Human Genetics. 81(3). 475–491. 210 indexed citations

Potier, Marie‐Claude, Isabelle Rivals, Grégoire Mercier, et al.. (2006). Transcriptional disruptions in Down syndrome: a case study in the Ts1Cje mouse cerebellum during post‐natal development. Journal of Neurochemistry. 97(s1). 104–109. 40 indexed citations

Nadrigny, Fabien, Isabelle Rivals, Petra G. Hirrlinger, et al.. (2006). Detecting fluorescent protein expression and co-localisation on single secretory vesicles with linear spectral unmixing. European Biophysics Journal. 35(6). 533–547. 32 indexed citations

Rivals, Isabelle, L. Personnaz, Lieng Taing, & Marie‐Claude Potier. (2006). Enrichment or depletion of a GO category within a class of genes: which test?. Bioinformatics. 23(4). 401–407. 496 indexed citations breakdown →

Dauphinot, Luce, Robert Lyle, Isabelle Rivals, et al.. (2004). The cerebellar transcriptome during postnatal development of the Ts1Cje mouse, a segmental trisomy model for Down syndrome. Human Molecular Genetics. 14(3). 373–384. 69 indexed citations

Rivals, Isabelle & L. Personnaz. (2003). Mlps (mono layer polynomials and multi layer perceptrons) for nonlinear modeling. Journal of Machine Learning Research. 3. 1383–1398. 40 indexed citations

Rivals, Isabelle & L. Personnaz. (2003). Neural-network construction and selection in nonlinear modeling. IEEE Transactions on Neural Networks. 14(4). 804–819. 68 indexed citations

Rivals, Isabelle & L. Personnaz. (2002). Response to the comments by J. Larsen and L.K. Hansen for:. Neural Networks. 15(1). 143–145. 1 indexed citations

Rivals, Isabelle & L. Personnaz. (2000). Construction of confidence intervals for neural networks based on least squares estimation. Neural Networks. 13(4-5). 463–484. 58 indexed citations

10.

Rivals, Isabelle & L. Personnaz. (2000). Nonlinear internal model control using neural networks: application to processes with delay and design issues. IEEE Transactions on Neural Networks. 11(1). 80–90. 110 indexed citations

11.

Personnaz, L. & Gérard Dreyfus. (1998). Comment on "Discrete-time recurrent neural network architectures: A unifying review".. Neurocomputing. 20. 325–331.

12.

Price, David J., S. Knerr, L. Personnaz, & Gérard Dreyfus. (1994). Pairwise Neural Network Classifiers with Probabilistic Outputs. 7. 1109–1116. 68 indexed citations

13.

Roussel-Ragot, P., et al.. (1994). Training recurrent neural networks: why and how? An illustration in dynamical process modeling. IEEE Transactions on Neural Networks. 5(2). 178–184. 85 indexed citations

14.

Roussel-Ragot, P., et al.. (1993). Neural Networks and Nonlinear Adaptive Filtering: Unifying Concepts and New Algorithms. Neural Computation. 5(2). 165–199. 116 indexed citations

15.

Knerr, S., L. Personnaz, & Gérard Dreyfus. (1992). Handwritten digit recognition by neural networks with single-layer training. IEEE Transactions on Neural Networks. 3(6). 962–968. 116 indexed citations

16.

Marcos, Sylvie, Odile Macchi, Christophe Vignat, et al.. (1992). A unified framework for gradient algorithms used for filter adaptation and neural network training. International Journal of Circuit Theory and Applications. 20(2). 159–200. 14 indexed citations

17.

Johannet, Anne, L. Personnaz, Gérard Dreyfus, Jean‐Dominique Gascuel, & M. Weinfeld. (1992). Specification and implementation of a digital Hopfield-type associative memory with on-chip training. IEEE Transactions on Neural Networks. 3(4). 529–539. 18 indexed citations

18.

Personnaz, L., Elie Bienenstock, & Gérard Dreyfus. (1989). A CURSORY INTRODUCTION TO THE PHYSICISTS' NEURAL NETWORKS. Le Journal de Physique Colloques. 50(C3). C3–207. 1 indexed citations

19.

Personnaz, L., Isabelle Guyon, Anne Johannet, Gérard Dreyfus, & G. Toulouse. (1986). A simple selectionist learning rule for neural networks. AIP conference proceedings. 151. 360–363.

20.

Personnaz, L., Isabelle Guyon, & Gérard Dreyfus. (1985). Information storage and retrieval in spin-glass like neural networks. Journal de Physique Lettres. 46(8). 359–365. 236 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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