Semi-supervised Penalized Output Kernel Regression for Link Prediction. - Céline Brouard; Florence d'Alché-Buc; Marie Szafranski (ICML, 2011)

Learning a Markov Logic network for supervised gene regulatory network inference. - Céline Brouard; Christel Vrain; Julie Dubois; David Castel; Marie-Anne Debily; Florence d'Alché-Buc (BMC Bioinform., 2013)

Inférence de réseaux d'interaction protéine-protéine par apprentissage statistique. (Protein-protein interaction network inference using statistical learning). - Céline Brouard (2013)

Soft Kernel Target Alignment for Two-Stage Multiple Kernel Learning. - Huibin Shen; Sándor Szedmák; Céline Brouard; Juho Rousu (DS, 2016)

Fast metabolite identification with Input Output Kernel Regression. - Céline Brouard; Huibin Shen; Kai Dührkop; Florence d'Alché-Buc; Sebastian Böcker; Juho Rousu (Bioinform., 2016)

Input Output Kernel Regression: Supervised and Semi-Supervised Structured Output Prediction with Operator-Valued Kernels. - Céline Brouard; Marie Szafranski; Florence d'Alché-Buc (J. Mach. Learn. Res., 2016)

Magnitude-Preserving Ranking for Structured Outputs. - Céline Brouard; Eric Bach 002; Sebastian Böcker; Juho Rousu (ACML, 2017)

Critical Assessment of Small Molecule Identification 2016: automated methods. - Emma Schymanski; Christoph Ruttkies; Martin Krauss; Céline Brouard; Tobias Kind; Kai Dührkop; Felicity Allen; Arpana Vaniya; Dries Verdegem; Sebastian Böcker; Juho Rousu; Huibin Shen; et al. (J. Cheminformatics, 2017)

Liquid-chromatography retention order prediction for metabolite identification. - Eric Bach 002; Sándor Szedmák; Céline Brouard; Sebastian Böcker; Juho Rousu (Bioinform., 2018)

Pushing Data into CP Models Using Graphical Model Learning and Solving. - Céline Brouard; Simon de Givry; Thomas Schiex (CP, 2020)

Learning Output Embeddings in Structured Prediction. - Luc Brogat-Motte; Alessandro Rudi; Céline Brouard; Juho Rousu; Florence d'Alché-Buc (CoRR, 2020)

Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters. - Luc Brogat-Motte; Rémi Flamary; Céline Brouard; Juho Rousu; Florence d'Alché-Buc (ICML, 2022)

Gene regulatory network inference methodology for genomic and transcriptomic data acquired in genetically related heterozygote individuals. - Lise Pomiès; Céline Brouard; Harold Duruflé; Élise Maigné; Clément Carré; Louise Gody; Fulya Trösser; George Katsirelos; Brigitte Mangin; Nicolas B. Langlade; Simon de Givry (Bioinform., 2022)

Vector-Valued Least-Squares Regression under Output Regularity Assumptions. - Luc Brogat-Motte; Alessandro Rudi; Céline Brouard; Juho Rousu; Florence d'Alché-Buc (J. Mach. Learn. Res., 2022)

Semi-supervised learning with pseudo-labeling compares favorably with large language models for regulatory sequence prediction. - Han Phan; Céline Brouard; Raphaël Mourad (Briefings Bioinform., 2024)

Should we really use graph neural networks for transcriptomic prediction? - Céline Brouard; Raphaël Mourad; Nathalie Vialaneix (Briefings Bioinform., 2024)