Léon Personnaz
Isabelle Rivals
Léon Personnaz
Lieng Taing
Marie-Claude Potier
Enrichment or depletion of a GO category within a class of genes: which test?
401-407
2007
23
Bioinform.
4
https://doi.org/10.1093/bioinformatics/btl633
https://www.wikidata.org/entity/Q34593379
db/journals/bioinformatics/bioinformatics23.html#RivalsPTP07
Isabelle Rivals
Léon Personnaz
Jacobian Conditioning Analysis for Model Validation.
401-418
2004
16
Neural Comput.
2
https://doi.org/10.1162/089976604322742083
https://www.wikidata.org/entity/Q52001893
db/journals/neco/neco16.html#RivalsP04
Isabelle Rivals
Léon Personnaz
MLPs (Mono-Layer Polynomials and Multi-Layer Perceptrons) for Nonlinear Modeling.
1383-1398
2003
3
J. Mach. Learn. Res.
http://jmlr.org/papers/v3/rivals03a.html
db/journals/jmlr/jmlr3.html#RivalsP03
Isabelle Rivals
Léon Personnaz
Neural-network construction and selection in nonlinear modeling.
804-819
2003
14
IEEE Trans. Neural Networks
4
https://doi.org/10.1109/TNN.2003.811356
https://www.wikidata.org/entity/Q80602245
db/journals/tnn/tnn14.html#RivalsP03
Isabelle Rivals
Léon Personnaz
No free lunch with the sandwich [sandwich estimator].
1553-1559
2003
14
IEEE Trans. Neural Networks
6
https://doi.org/10.1109/TNN.2003.820671
https://www.wikidata.org/entity/Q80618314
db/journals/tnn/tnn14.html#RivalsP03a
Isabelle Rivals
Léon Personnaz
Construction of confidence intervals for neural networks based on least squares estimation.
463-484
2000
13
Neural Networks
4-5
https://doi.org/10.1016/S0893-6080(99)00080-5
https://www.wikidata.org/entity/Q52075154
db/journals/nn/nn13.html#RivalsP00
Isabelle Rivals
Léon Personnaz
Nonlinear internal model control using neural networks: application to processes with delay and design issues.
80-90
2000
11
IEEE Trans. Neural Networks Learn. Syst.
1
https://doi.org/10.1109/72.822512
https://www.wikidata.org/entity/Q80631919
db/journals/tnn/tnn11.html#RivalsP00
Isabelle Rivals
Léon Personnaz
On Cross Validation for Model Selection.
863-870
1999
11
Neural Comput.
4
db/journals/neco/neco11.html#RivalsP99
https://doi.org/10.1162/089976699300016476
https://www.wikidata.org/entity/Q52216300
L. Constant
B. Dagues
Isabelle Rivals
Léon Personnaz
Undersampling for the training of feedback neural networks on large sequences; application to the modeling of an induction machine.
1025-1028
1999
ICECS
https://doi.org/10.1109/ICECS.1999.813408
conf/icecsys/1999
db/conf/icecsys/icecsys1999.html#ConstantDRP99
Yacine Oussar
Isabelle Rivals
Léon Personnaz
Gérard Dreyfus
Training wavelet networks for nonlinear dynamic input-output modeling.
173-188
1998
20
Neurocomputing
1-3
https://doi.org/10.1016/S0925-2312(98)00010-1
db/journals/ijon/ijon20.html#OussarRPD98
Isabelle Rivals
Léon Personnaz
A recursive algorithm based on the extended Kalman filter for the training of feedforward neural models.
279-294
1998
20
Neurocomputing
1-3
https://doi.org/10.1016/S0925-2312(98)00021-6
db/journals/ijon/ijon20.html#RivalsP98
Léon Personnaz
Gérard Dreyfus
Comment on "Recurrent neural networks: A constructive algorithm, and its properties".
321-324
1998
20
Neurocomputing
1-3
db/journals/ijon/ijon20.html#PersonnazD98
Léon Personnaz
Gérard Dreyfus
Comment on "Discrete-time recurrent neural network architectures: A unifying review".
325-331
1998
20
Neurocomputing
1-3
db/journals/ijon/ijon20.html#PersonnazD98a
Olivier Nerrand
Pierre Roussel-Ragot
Dominique Urbani
Léon Personnaz
Gérard Dreyfus
Training recurrent neural networks: why and how? An illustration in dynamical process modeling.
178-184
1994
5
IEEE Trans. Neural Networks
2
https://doi.org/10.1109/72.279183
https://www.wikidata.org/entity/Q52383603
db/journals/tnn/tnn5.html#NerrandRUPD94
David Price
Stefan Knerr
Léon Personnaz
Gérard Dreyfus
Pairwise Neural Network Classifiers with Probabilistic Outputs.
1109-1116
http://papers.nips.cc/paper/883-pairwise-neural-network-classifiers-with-probabilistic-outputs
http://nips.djvuzone.org/djvu/nips07/1109.djvu
1994
conf/nips/1994
NIPS
db/conf/nips/nips1994.html#PriceKPD94
Olivier Nerrand
Pierre Roussel-Ragot
Léon Personnaz
Gérard Dreyfus
Sylvie Marcos
Neural Networks and Nonlinear Adaptive Filtering: Unifying Concepts and New Algorithms.
165-199
1993
5
Neural Comput.
2
https://doi.org/10.1162/neco.1993.5.2.165
db/journals/neco/neco5.html#NerrandRPDM93
Christiane Linster
Claudine Masson
Michel Kerszberg
Léon Personnaz
Gérard Dreyfus
Computational Diversity in a Formal Model of the Insect Olfactory Macroglomerulus.
228-241
1993
5
Neural Comput.
2
https://doi.org/10.1162/neco.1993.5.2.228
db/journals/neco/neco5.html#LinsterMKPG93
Sylvie Marcos
Odile Macchi
Christophe Vignat
Gérard Dreyfus
Léon Personnaz
Pierre Roussel-Ragot
A unified framework for gradient algorithms used for filter adaptation and neural network training.
159-200
1992
20
Int. J. Circuit Theory Appl.
2
https://doi.org/10.1002/cta.4490200205
db/journals/ijcta/ijcta20.html#MarcosMVDPR92
Anne Johannet
Léon Personnaz
Gérard Dreyfus
Jean-Dominique Gascuel
Michel Weinfeld
Specification and implementation of a digital Hopfield-type associative memory with on-chip training.
529-539
1992
3
IEEE Trans. Neural Networks
4
https://doi.org/10.1109/72.143369
https://www.wikidata.org/entity/Q39834703
db/journals/tnn/tnn3.html#JohannetPDGW92
Stefan Knerr
Léon Personnaz
Gérard Dreyfus
Handwritten digit recognition by neural networks with single-layer training.
962-968
1992
3
IEEE Trans. Neural Networks
6
https://doi.org/10.1109/72.165597
https://www.wikidata.org/entity/Q52233291
db/journals/tnn/tnn3.html#KnerrPD92
Christiane Linster
David Marsan
Claudine Masson
Michel Kerszberg
Gérard Dreyfus
Léon Personnaz
A Formal Model of the Insect Olfactory Macroglomerulus: Simulations and Analytic Results.
1022-1029
http://papers.nips.cc/paper/677-a-formal-model-of-the-insect-olfactory-macroglomerulus-simulations-and-analytic-results
http://nips.djvuzone.org/djvu/nips05/1022.djvu
1992
conf/nips/1992
NIPS
db/conf/nips/nips1992.html#LinsterMMKDP92
Léon Personnaz
Gérard Dreyfus
Neural Network Models and Applications: an Overview.
1-8
1990
conf/ifip7/1990
Modelling the Innovation
db/conf/ifip7/ifip7-1990.html#PersonnazD90
Léon Personnaz
Gérard Dreyfus
Neurocomputing in France.
35-36
1989
1
Neurocomputing
1
db/journals/ijon/ijon1.html#PersonnazD89
https://doi.org/10.1016/S0925-2312(89)80017-7
Stefan Knerr
Léon Personnaz
Gérard Dreyfus
Single-layer learning revisited: a stepwise procedure for building and training a neural network.
41-50
1989
NATO Neurocomputing
https://doi.org/10.1007/978-3-642-76153-9_5
conf/nato/1989
db/conf/nato/neuro1989.html#KnerrPD89
Gérard Dreyfus
Isabelle Guyon
Jean-Pierre Nadal
Léon Personnaz
High Order Neural Networks for Efficient Associative Memory Design.
233-241
http://papers.nips.cc/paper/87-high-order-neural-networks-for-efficient-associative-memory-design
http://nips.djvuzone.org/djvu/nips00/0233.djvu
1987
conf/nips/1987
NIPS
db/conf/nips/nips1987.html#DreyfusGNP87
L. Constant
B. Dagues
Gérard Dreyfus
Jean-Dominique Gascuel
Isabelle Guyon
Anne Johannet
Michel Kerszberg
Stefan Knerr
Christiane Linster
Odile Macchi
Sylvie Marcos
David Marsan
Claudine Masson
Jean-Pierre Nadal
Olivier Nerrand
Yacine Oussar
Marie-Claude Potier
David Price
Isabelle Rivals
Pierre Roussel-Ragot
Lieng Taing
Dominique Urbani
Christophe Vignat
Michel Weinfeld