Céline Brouard

19 papers A* 2A 1B 1C 1Journal 13

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	NMFProfiler: a multi-omics integration method for samples stratified in groups. Bioinform. Aurélie Mercadié, Éléonore Gravier, Gwendal Josse, Isabelle Fournier, Cécile Viodé, Nathalie Vialaneix, Céline Brouard
2024	J	`jnl`	Semi-supervised learning with pseudo-labeling compares favorably with large language models for regulatory sequence prediction. Briefings Bioinform. Han Phan, Céline Brouard, Raphaël Mourad
2024	J	`jnl`	Should we really use graph neural networks for transcriptomic prediction? Briefings Bioinform. Céline Brouard, Raphaël Mourad, Nathalie Vialaneix
2022	J	`jnl`	Gene regulatory network inference methodology for genomic and transcriptomic data acquired in genetically related heterozygote individuals. Bioinform. Lise Pomiès, Céline Brouard, Harold Duruflé, Élise Maigné, Clément Carré, Louise Gody, Fulya Trösser, George Katsirelos, Brigitte Mangin, Nicolas B. Langlade, Simon de Givry
2022	A*	`conf`	Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters. ICML Luc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc
2022	J	`jnl`	Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters. CoRR Luc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc
2022	J	`jnl`	Vector-Valued Least-Squares Regression under Output Regularity Assumptions. CoRR Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc
2022	J	`jnl`	Vector-Valued Least-Squares Regression under Output Regularity Assumptions. J. Mach. Learn. Res. Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc
2020	J	`jnl`	Learning Output Embeddings in Structured Prediction. CoRR Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc
2020	A	`conf`	Pushing Data into CP Models Using Graphical Model Learning and Solving. CP Céline Brouard, Simon de Givry, Thomas Schiex
2018	J	`jnl`	Liquid-chromatography retention order prediction for metabolite identification. Bioinform. Eric Bach, Sándor Szedmák, Céline Brouard, Sebastian Böcker, Juho Rousu
2017	J	`jnl`	Critical Assessment of Small Molecule Identification 2016: automated methods. J. Cheminformatics Emma Schymanski, Christoph Ruttkies, Martin Krauss, Céline Brouard, Tobias Kind, Kai Dührkop, Felicity Allen, Arpana Vaniya, Dries Verdegem, Sebastian Böcker, Juho Rousu, Huibin Shen, Hiroshi Tsugawa, Tanvir Sajed, Oliver Fiehn, Bart Ghesquière, Steffen Neumann
2017	C	`conf`	Magnitude-Preserving Ranking for Structured Outputs. ACML Céline Brouard, Eric Bach, Sebastian Böcker, Juho Rousu
2016	J	`jnl`	Fast metabolite identification with Input Output Kernel Regression. Bioinform. Céline Brouard, Huibin Shen, Kai Dührkop, Florence d'Alché-Buc, Sebastian Böcker, Juho Rousu
2016	J	`jnl`	Input Output Kernel Regression: Supervised and Semi-Supervised Structured Output Prediction with Operator-Valued Kernels. J. Mach. Learn. Res. Céline Brouard, Marie Szafranski, Florence d'Alché-Buc
2016	B	`conf`	Soft Kernel Target Alignment for Two-Stage Multiple Kernel Learning. DS Huibin Shen, Sándor Szedmák, Céline Brouard, Juho Rousu
2013	—	`—`	Inférence de réseaux d'interaction protéine-protéine par apprentissage statistique. (Protein-protein interaction network inference using statistical learning). Céline Brouard
2013	J	`jnl`	Learning a Markov Logic network for supervised gene regulatory network inference. BMC Bioinform. Céline Brouard, Christel Vrain, Julie Dubois, David Castel, Marie-Anne Debily, Florence d'Alché-Buc
2011	A*	`conf`	Semi-supervised Penalized Output Kernel Regression for Link Prediction. ICML Céline Brouard, Florence d'Alché-Buc, Marie Szafranski