Gérard Biau

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 26

Top Topics

Randomized Trees

Top Venues

J. Mach. Learn. Res.

Publications

Pierre Marion, Yu-Han Wu, Michael Eli Sander, Gérard Biau
Implicit regularization of deep residual networks towards neural ODEs. ICLR (2024)
Nathan Doumèche, Francis Bach, Claire Boyer, Gérard Biau
Physics-informed machine learning as a kernel method. CoRR (2024)
Nathan Doumèche, Francis Bach, Gérard Biau, Claire Boyer
Physics-informed machine learning as a kernel method. COLT (2024)
Pierre Marion, Yu-Han Wu, Michael E. Sander, Gérard Biau
Implicit regularization of deep residual networks towards neural ODEs. CoRR (2023)
Pierre Marion, Adeline Fermanian, Gérard Biau, Jean-Philippe Vert
Scaling ResNets in the Large-depth Regime. CoRR (2022)
Arthur Stéphanovitch, Ugo Tanielian, Benoît Cadre, Nicolas Klutchnikoff, Gérard Biau
Optimal 1-Wasserstein Distance for WGANs. CoRR (2022)
Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
SHAFF: Fast and consistent SHApley eFfect estimates via random Forests. AISTATS (2022)
Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
Interpretable Random Forests via Rule Extraction. AISTATS (2021)
Adeline Fermanian, Pierre Marion, Jean-Philippe Vert, Gérard Biau
Framing RNN as a kernel method: A neural ODE approach. NeurIPS (2021)
Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
SHAFF: Fast and consistent SHApley eFfect estimates via random Forests. CoRR (2021)
Ugo Tanielian, Gérard Biau
Approximating Lipschitz continuous functions with GroupSort neural networks. AISTATS (2021)
Adeline Fermanian, Pierre Marion, Jean-Philippe Vert, Gérard Biau
Framing RNN as a kernel method: A neural ODE approach. CoRR (2021)
Qiming Du, Gérard Biau, François Petit, Raphaël Porcher
Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects. AISTATS (2021)
Gérard Biau, Maxime Sangnier, Ugo Tanielian
Some Theoretical Insights into Wasserstein GANs. J. Mach. Learn. Res. 22 (2021)
Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
Interpretable Random Forests via Rule Extraction. CoRR (2020)
Qiming Du, Gérard Biau, François Petit, Raphaël Porcher
Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects. CoRR (2020)
Gérard Biau, Maxime Sangnier, Ugo Tanielian
Some Theoretical Insights into Wasserstein GANs. CoRR (2020)
Ugo Tanielian, Maxime Sangnier, Gérard Biau
Approximating Lipschitz continuous functions with GroupSort neural networks. CoRR (2020)
Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
SIRUS: making random forests interpretable. CoRR (2019)
Gérard Biau, Benoît Cadre, Laurent Rouvìère
Accelerated gradient boosting. Mach. Learn. 108 (6) (2019)
Gérard Biau, Benoît Cadre, Laurent Rouvìère
Accelerated Gradient Boosting. CoRR (2018)
Gérard Biau, Benoît Cadre, Maxime Sangnier, Ugo Tanielian
Some Theoretical Properties of GANs. CoRR (2018)
Gérard Biau, Benoît Cadre
Optimization by gradient boosting. CoRR (2017)
Gérard Biau, Erwan Scornet, Johannes Welbl
Neural Random Forests. CoRR (2016)
Gérard Biau, Aurélie Fischer, Benjamin Guedj, James D. Malley
COBRA: A combined regression strategy. J. Multivar. Anal. 146 (2016)
Gérard Biau, Kevin Bleakley, Benoît Cadre
The Statistical Performance of Collaborative Inference. J. Mach. Learn. Res. 17 (2016)
Gérard Biau, Luc Devroye
Cellular Tree Classifiers. ALT (2014)
Gérard Biau, Luc Devroye
Cellular Tree Classifiers CoRR (2013)
Pierre Alquier, Gérard Biau
Sparse single-index model. J. Mach. Learn. Res. 14 (1) (2013)
Gérard Biau, Adam Krzyzak, Luc Devroye, Vida Dujmovic
An affine invariant k-nearest neighbor regression estimate. ISIT (2012)
Gérard Biau, Aurélie Fischer
Parameter Selection for Principal Curves. IEEE Trans. Inf. Theory 58 (3) (2012)
Gérard Biau, Luc Devroye, Vida Dujmovic, Adam Krzyzak
An affine invariant k-nearest neighbor regression estimate. J. Multivar. Anal. 112 (2012)
Gérard Biau
Analysis of a Random Forests Model. J. Mach. Learn. Res. 13 (2012)
Gérard Biau, Benoît Patra
Sequential Quantile Prediction of Time Series. IEEE Trans. Inf. Theory 57 (3) (2011)
Gérard Biau, Frédéric Cérou, Arnaud Guyader
Rates of convergence of the functional k-nearest neighbor estimate. IEEE Trans. Inf. Theory 56 (4) (2010)
Gérard Biau, Luc Devroye
On the layered nearest neighbour estimate, the bagged nearest neighbour estimate and the random forest method in regression and classification. J. Multivar. Anal. 101 (10) (2010)
Gérard Biau, Frédéric Cérou, Arnaud Guyader
On the Rate of Convergence of the Bagged Nearest Neighbor Estimate. J. Mach. Learn. Res. 11 (2010)
Gérard Biau, Luc Devroye, Gábor Lugosi
Consistency of Random Forests and Other Averaging Classifiers. J. Mach. Learn. Res. 9 (2008)
Kevin Bleakley, Marie-Paule Lefranc, Gérard Biau
Recovering probabilities for nucleotide trimming processes for T cell receptor TRA and TRG V-J junctions analyzed with IMGT tools. BMC Bioinform. 9 (2008)
Gérard Biau, Luc Devroye, Gábor Lugosi
On the Performance of Clustering in Hilbert Spaces. IEEE Trans. Inf. Theory 54 (2) (2008)
Kevin Bleakley, Gérard Biau, Jean-Philippe Vert
Supervised reconstruction of biological networks with local models. ISMB/ECCB (Supplement of Bioinformatics) (2007)
Kevin Bleakley, Véronique Giudicelli, Yan Wu, Marie-Paule Lefranc, Gérard Biau
IMGT Standardization for Statistical Analyses of T Cell Receptor Junctions: The TRAV-TRAJ Example. Silico Biol. 6 (6) (2006)
Gérard Biau, Florentina Bunea, Marten H. Wegkamp
Functional classification in Hilbert spaces. IEEE Trans. Inf. Theory 51 (6) (2005)
Gérard Biau, László Györfi
-test statistic of homogeneity. IEEE Trans. Inf. Theory 51 (11) (2005)
Gérard Biau, Luc Devroye
A note on density model size testing. IEEE Trans. Inf. Theory 50 (3) (2004)