L. Personnaz
- Artificial Intelligence top 1%
- Molecular Biology
- Control and Systems Engineering top 2%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Isabelle RivalsGérard DreyfusMarie‐Claude PotierLieng TaingIsabelle GuyonS. KnerrP. Roussel-RagotYacine Oussar
- Topics
- Neural Networks and Applications (34 papers)Control Systems and Identification (13 papers)Fault Detection and Control Systems (11 papers)
In The Last Decade
L. Personnaz
41 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 167
- Artificial Intelligence 1.1k
- Molecular Biology 553
- Control and Systems Engineering 455
- Electrical and Electronic Engineering 272
- Computer Vision and Pattern Recognition 250
Countries citing papers authored by L. Personnaz
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 210 | |
| 2 | 40 | |
| 3 | Enrichment or depletion of a GO category within a class of genes: which test?breakdown → | 496 |
| 4 | 32 | |
| 5 | 69 | |
| 6 | Mlps (mono layer polynomials and multi layer perceptrons) for nonlinear modeling | 40 |
| 7 | 68 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 58 | |
| 11 | 110 | |
| 12 | Comment on "Discrete-time recurrent neural network architectures: A unifying review". | 0 |
| 13 | 85 | |
| 14 | Pairwise Neural Network Classifiers with Probabilistic Outputs | 68 |
| 15 | 116 | |
| 16 | 18 | |
| 17 | 116 | |
| 18 | 14 | |
| 19 | 0 | |
| 20 | 236 |
About L. Personnaz
L. Personnaz is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 44 papers that have together received 2.5k indexed citations. Recurring topics across this work include Neural Networks and Applications (34 papers), Control Systems and Identification (13 papers) and Fault Detection and Control Systems (11 papers). The work is most often cited by research in Artificial Intelligence (1.1k citations), Control and Systems Engineering (455 citations) and Computer Vision and Pattern Recognition (250 citations). L. Personnaz has collaborated with scholars based in France and Germany. Frequent 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. Their work appears in journals such as Bioinformatics, Journal of Neurochemistry and The American Journal of Human Genetics.
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.