Céline Brouard
Céline Brouard
INRAE, MIA Toulouse, France
Verified email at inra.fr - Homepage
Title
Cited by
Cited by
Year
Critical assessment of small molecule identification 2016: automated methods
EL Schymanski, C Ruttkies, M Krauss, C Brouard, T Kind, K Dührkop, ...
Journal of cheminformatics 9 (1), 1-21, 2017
1002017
Semi-supervised penalized output kernel regression for link prediction
C Brouard, F d'Alché-Buc, M Szafranski
Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011
782011
Fast metabolite identification with input output kernel regression
C Brouard, H Shen, K Dührkop, F d'Alché-Buc, S Böcker, J Rousu
Bioinformatics 32 (12), i28-i36, 2016
532016
Input output kernel regression: Supervised and semi-supervised structured output prediction with operator-valued kernels
C Brouard, M Szafranski, F d'Alché-Buc
Journal of Machine Learning Research 17, np, 2016
412016
Liquid-chromatography retention order prediction for metabolite identification
E Bach, S Szedmak, C Brouard, S Böcker, J Rousu
Bioinformatics 34 (17), i875-i883, 2018
222018
Learning a Markov Logic network for supervised gene regulatory network inference
C Brouard, C Vrain, J Dubois, D Castel, MA Debily, F d’Alché-Buc
BMC bioinformatics 14 (1), 1-14, 2013
162013
Magnitude-preserving ranking for structured outputs
C Brouard, E Bach, S Böcker, J Rousu
Asian Conference on Machine Learning, 407-422, 2017
102017
Machine learning of protein interactions in fungal secretory pathways
J Kludas, M Arvas, S Castillo, T Pakula, M Oja, C Brouard, J Jäntti, ...
PloS one 11 (7), e0159302, 2016
72016
Inférence de réseaux d'interaction protéine-protéine par apprentissage statistique
C Brouard
Université d'Évry-Val-d'Essonne, 2013
62013
Improved small molecule identification through learning combinations of kernel regression models
C Brouard, A Bassé, F d’Alché-Buc, J Rousu
Metabolites 9 (8), 160, 2019
32019
Critical assessment of small molecule identification 2016: automated methods. J Cheminform 9 (1): 22
EL Schymanski, C Ruttkies, M Krauss, C Brouard, T Kind, K Dührkop
32017
Regularized output kernel regression applied to protein-protein interaction network inference
C Brouard, M Szafranski, F d’Alché-Buc
NIPS MLCB Workshop, 2010
32010
Soft kernel target alignment for two-stage multiple kernel learning
H Shen, S Szedmak, C Brouard, J Rousu
International Conference on Discovery Science, 427-441, 2016
22016
Protein-protein interaction network inference with semi-supervised Output Kernel Regression
C Brouard, M Szafranski, F d'Alché-Buc
JOBIM, 133-136, 2012
22012
Pushing Data into CP Models Using Graphical Model Learning and Solving
C Brouard, S de Givry, T Schiex
International Conference on Principles and Practice of Constraint …, 2020
2020
Learning Output Embeddings in Structured Prediction
L Brogat-Motte, A Rudi, C Brouard, J Rousu, F d'Alché-Buc
arXiv preprint arXiv:2007.14703, 2020
2020
RNA expression dataset of 384 sunflower hybrids in field condition
C Penouilh-Suzette, L Pomiès, H Duruflé, N Blanchet, F Bonnafous, ...
OCL 27, 36, 2020
2020
Unsupervised variable selection for kernel methods in systems biology
J Mariette, C Brouard, R Flamary, N Vialaneix
Journée Régionale de Bioinformatique et Biostatistique, Génopole Toulouse, 2019
2019
Markov Logic Network for supervised gene regulation inference: application to the ID2 regulatory network in human keratinocytes
C Brouard, J Dubois, C Vrain, D Castel, MA Debily, F d'Alché-Buc
International Workshop on Machine Learning in Systems Biology, 2012
2012
A new theoretical angle to semi-supervised output kernel regression for protein-protein interaction network inference
C Brouard, F d'Alché-Buc, M Szafranski
International Workshop on Machine Learning in Systems Biology, 2011
2011
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Articles 1–20