Gérard Biau

According to our database, Gérard Biau authored at least 37 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Attention layers provably solve single-location regression.

Pierre Marion, Raphaël Berthier, Gérard Biau, Claire Boyer

CoRR, 2024

Physics-informed kernel learning.

Nathan Doumèche, Francis Bach, Gérard Biau, Claire Boyer

CoRR, 2024

Implicit regularization of deep residual networks towards neural ODEs.

Pierre Marion, Yu-Han Wu, Michael Eli Sander, Gérard Biau

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Physics-informed machine learning as a kernel method.

Nathan Doumèche, Francis Bach, Gérard Biau, Claire Boyer

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2022

Scaling ResNets in the Large-depth Regime.

Pierre Marion, Adeline Fermanian, Gérard Biau, Jean-Philippe Vert

CoRR, 2022

Optimal 1-Wasserstein Distance for WGANs.

Arthur Stéphanovitch, Ugo Tanielian, Benoît Cadre, Nicolas Klutchnikoff, Gérard Biau

CoRR, 2022

SHAFF: Fast and consistent SHApley eFfect estimates via random Forests.

Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Some Theoretical Insights into Wasserstein GANs.

Gérard Biau, Maxime Sangnier, Ugo Tanielian

J. Mach. Learn. Res., 2021

Framing RNN as a kernel method: A neural ODE approach.

Adeline Fermanian, Pierre Marion, Jean-Philippe Vert, Gérard Biau

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Approximating Lipschitz continuous functions with GroupSort neural networks.

Ugo Tanielian, Gérard Biau

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects.

Qiming Du, Gérard Biau, François Petit, Raphaël Porcher

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Interpretable Random Forests via Rule Extraction.

Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Approximating Lipschitz continuous functions with GroupSort neural networks.

Ugo Tanielian, Maxime Sangnier, Gérard Biau

CoRR, 2020

2019

Accelerated gradient boosting.

Gérard Biau, Benoît Cadre, Laurent Rouvìère

Mach. Learn., 2019

SIRUS: making random forests interpretable.

Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet

CoRR, 2019

2018

Some Theoretical Properties of GANs.

Gérard Biau, Benoît Cadre, Maxime Sangnier, Ugo Tanielian

CoRR, 2018

2017

Optimization by gradient boosting.

Gérard Biau, Benoît Cadre

CoRR, 2017

2016

COBRA: A combined regression strategy.

Gérard Biau, Aurélie Fischer, Benjamin Guedj, James D. Malley

J. Multivar. Anal., 2016

The Statistical Performance of Collaborative Inference.

Gérard Biau, Kevin Bleakley, Benoît Cadre

J. Mach. Learn. Res., 2016

Neural Random Forests.

Gérard Biau, Erwan Scornet, Johannes Welbl

CoRR, 2016

2014

Cellular Tree Classifiers.

Gérard Biau, Luc Devroye

Proceedings of the Algorithmic Learning Theory - 25th International Conference, 2014

2013

Sparse single-index model.

Pierre Alquier, Gérard Biau

J. Mach. Learn. Res., 2013

2012

Parameter Selection for Principal Curves.

Gérard Biau, Aurélie Fischer

IEEE Trans. Inf. Theory, 2012

An affine invariant k-nearest neighbor regression estimate.

Gérard Biau, Luc Devroye, Vida Dujmovic, Adam Krzyzak

J. Multivar. Anal., 2012

Analysis of a Random Forests Model.

Gérard Biau

J. Mach. Learn. Res., 2012

2011

Sequential Quantile Prediction of Time Series.

Gérard Biau, Benoît Patra

IEEE Trans. Inf. Theory, 2011

2010

Rates of convergence of the functional k-nearest neighbor estimate.

Gérard Biau, Frédéric Cérou, Arnaud Guyader

IEEE Trans. Inf. Theory, 2010

On the layered nearest neighbour estimate, the bagged nearest neighbour estimate and the random forest method in regression and classification.

Gérard Biau, Luc Devroye

J. Multivar. Anal., 2010

On the Rate of Convergence of the Bagged Nearest Neighbor Estimate.

Gérard Biau, Frédéric Cérou, Arnaud Guyader

J. Mach. Learn. Res., 2010

2008

On the Performance of Clustering in Hilbert Spaces.

Gérard Biau, Luc Devroye, Gábor Lugosi

IEEE Trans. Inf. Theory, 2008

Consistency of Random Forests and Other Averaging Classifiers.

Gérard Biau, Luc Devroye, Gábor Lugosi

J. Mach. Learn. Res., 2008

Recovering probabilities for nucleotide trimming processes for T cell receptor TRA and TRG V-J junctions analyzed with IMGT tools.

Kevin Bleakley, Marie-Paule Lefranc, Gérard Biau

BMC Bioinform., 2008

2007

Supervised reconstruction of biological networks with local models.

Kevin Bleakley, Gérard Biau, Jean-Philippe Vert

Proceedings of the Proceedings 15th International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB), 2007

2006

IMGT Standardization for Statistical Analyses of T Cell Receptor Junctions: The TRAV-TRAJ Example.

Kevin Bleakley, Véronique Giudicelli, Yan Wu, Marie-Paule Lefranc, Gérard Biau

Silico Biol., 2006

2005

On the asymptotic properties of a nonparametric L₁-test statistic of homogeneity.

Gérard Biau, László Györfi

IEEE Trans. Inf. Theory, 2005

Functional classification in Hilbert spaces.

Gérard Biau, Florentina Bunea, Marten H. Wegkamp

IEEE Trans. Inf. Theory, 2005

2004

A note on density model size testing.

Gérard Biau, Luc Devroye

IEEE Trans. Inf. Theory, 2004