Florence d'Alché-Buc

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A Functional Extension of Multi-Output Learning

Z. Szabó, Alex Lambert, Romain Brault, 2019 .

Parametric Estimation of Ordinary Differential Equations

N. Brunel, Q. Clairon, Florence d'Alché-Buc, 2012 .

Functional Output Regression with Infimal Convolution: Exploring the Huber and ε-insensitive Losses

Z. Szabó, Alex Lambert, Florence d'Alché-Buc, 2022, ArXiv.

Functional Output Regression with Inﬁmal Convolution: Exploring the Huber and (cid:15) -insensitive Losses

Z. Szabó, Alex Lambert, Florence d'Alché-Buc, 2022 .

A methodology for topographic clustering of structured text documents

Marie-Jeanne Lesot, Florence d'Alché-Buc, Delphine Dard, 2004 .

Depth-based pseudo-metrics between probability distributions pdf

Stéphan Clémençon, Pavlo Mozharovskyi, Guillaume Staerman, 2021, ArXiv.

Improved Small Molecule Identification through Learning Combinations of Kernel Regression Models

Juho Rousu, Céline Brouard, Antoine Bassé, 2019, Metabolites.

A Framework to Learn with Interpretation

Pavlo Mozharovskyi, Florence d'Alché-Buc, Jayneel Parekh, 2020, NeurIPS.

Estimating parameters and hidden variables in non-linear state-space models based on ODEs for biological networks inference

N. Brunel, Florence d'Alché-Buc, Minh Quach, 2007, Bioinform..