Gérard Biau - RankMe

55 papers A* 5A 4B 2Journal 43Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Attention layers provably solve single-location regression. ICLR Pierre Marion, Raphaël Berthier, Gérard Biau, Claire Boyer
2025	J	`jnl`	Fast kernel methods: Sobolev, physics-informed, and additive models. CoRR Nathan Doumèche, Francis Bach, Gérard Biau, Claire Boyer
2025	J	`jnl`	Forecasting time series with constraints. CoRR Nathan Doumèche, Francis R. Bach, Éloi Bedek, Gérard Biau, Claire Boyer, Yannig Goude
2025	J	`jnl`	Optimal Stopping in Latent Diffusion Models. CoRR Yu-Han Wu, Quentin Berthet, Gérard Biau, Claire Boyer, Romuald Elie, Pierre Marion
2025	J	`jnl`	Physics-informed Kernel Learning. J. Mach. Learn. Res. Nathan Doumèche, Francis Bach, Gérard Biau, Claire Boyer
2025	J	`jnl`	Scaling ResNets in the Large-depth Regime. J. Mach. Learn. Res. Pierre Marion, Adeline Fermanian, Gérard Biau, Jean-Philippe Vert
2025	A*	`conf`	Taking a Big Step: Large Learning Rates in Denoising Score Matching Prevent Memorization. COLT Yu-Han Wu, Pierre Marion, Gérard Biau, Claire Boyer
2025	J	`jnl`	Taking a Big Step: Large Learning Rates in Denoising Score Matching Prevent Memorization. CoRR Yu-Han Wu, Pierre Marion, Gérard Biau, Claire Boyer
2024	J	`jnl`	Attention layers provably solve single-location regression. CoRR Pierre Marion, Raphaël Berthier, Gérard Biau, Claire Boyer
2024	A*	`conf`	Implicit regularization of deep residual networks towards neural ODEs. ICLR Pierre Marion, Yu-Han Wu, Michael Eli Sander, Gérard Biau
2024	J	`jnl`	Physics-informed kernel learning. CoRR Nathan Doumèche, Francis R. Bach, Gérard Biau, Claire Boyer
2024	A*	`conf`	Physics-informed machine learning as a kernel method. COLT Nathan Doumèche, Francis R. Bach, Gérard Biau, Claire Boyer
2024	J	`jnl`	Physics-informed machine learning as a kernel method. CoRR Nathan Doumèche, Francis R. Bach, Claire Boyer, Gérard Biau
2023	J	`jnl`	Implicit regularization of deep residual networks towards neural ODEs. CoRR Pierre Marion, Yu-Han Wu, Michael E. Sander, Gérard Biau
2022	J	`jnl`	Optimal 1-Wasserstein Distance for WGANs. CoRR Arthur Stéphanovitch, Ugo Tanielian, Benoît Cadre, Nicolas Klutchnikoff, Gérard Biau
2022	A	`conf`	SHAFF: Fast and consistent SHApley eFfect estimates via random Forests. AISTATS Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
2022	J	`jnl`	Scaling ResNets in the Large-depth Regime. CoRR Pierre Marion, Adeline Fermanian, Gérard Biau, Jean-Philippe Vert
2021	A	`conf`	Approximating Lipschitz continuous functions with GroupSort neural networks. AISTATS Ugo Tanielian, Gérard Biau
2021	A*	`conf`	Framing RNN as a kernel method: A neural ODE approach. NeurIPS Adeline Fermanian, Pierre Marion, Jean-Philippe Vert, Gérard Biau
2021	J	`jnl`	Framing RNN as a kernel method: A neural ODE approach. CoRR Adeline Fermanian, Pierre Marion, Jean-Philippe Vert, Gérard Biau
2021	A	`conf`	Interpretable Random Forests via Rule Extraction. AISTATS Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
2021	J	`jnl`	SHAFF: Fast and consistent SHApley eFfect estimates via random Forests. CoRR Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
2021	J	`jnl`	Some Theoretical Insights into Wasserstein GANs. J. Mach. Learn. Res. Gérard Biau, Maxime Sangnier, Ugo Tanielian
2021	A	`conf`	Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects. AISTATS Qiming Du, Gérard Biau, François Petit, Raphaël Porcher
2020	J	`jnl`	Approximating Lipschitz continuous functions with GroupSort neural networks. CoRR Ugo Tanielian, Maxime Sangnier, Gérard Biau
2020	J	`jnl`	Interpretable Random Forests via Rule Extraction. CoRR Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
2020	J	`jnl`	Some Theoretical Insights into Wasserstein GANs. CoRR Gérard Biau, Maxime Sangnier, Ugo Tanielian
2020	J	`jnl`	Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects. CoRR Qiming Du, Gérard Biau, François Petit, Raphaël Porcher
2019	J	`jnl`	Accelerated gradient boosting. Mach. Learn. Gérard Biau, Benoît Cadre, Laurent Rouvìère
2019	J	`jnl`	SIRUS: making random forests interpretable. CoRR Clément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet
2018	J	`jnl`	Accelerated Gradient Boosting. CoRR Gérard Biau, Benoît Cadre, Laurent Rouvìère
2018	J	`jnl`	Some Theoretical Properties of GANs. CoRR Gérard Biau, Benoît Cadre, Maxime Sangnier, Ugo Tanielian
2017	J	`jnl`	Optimization by gradient boosting. CoRR Gérard Biau, Benoît Cadre
2016	J	`jnl`	COBRA: A combined regression strategy. J. Multivar. Anal. Gérard Biau, Aurélie Fischer, Benjamin Guedj, James D. Malley
2016	J	`jnl`	Neural Random Forests. CoRR Gérard Biau, Erwan Scornet, Johannes Welbl
2016	J	`jnl`	The Statistical Performance of Collaborative Inference. J. Mach. Learn. Res. Gérard Biau, Kevin Bleakley, Benoît Cadre
2014	B	`conf`	Cellular Tree Classifiers. ALT Gérard Biau, Luc Devroye
2013	J	`jnl`	Cellular Tree Classifiers CoRR Gérard Biau, Luc Devroye
2013	J	`jnl`	Sparse single-index model. J. Mach. Learn. Res. Pierre Alquier, Gérard Biau
2012	B	`conf`	An affine invariant k-nearest neighbor regression estimate. ISIT Gérard Biau, Adam Krzyzak, Luc Devroye, Vida Dujmovic
2012	J	`jnl`	An affine invariant k-nearest neighbor regression estimate. J. Multivar. Anal. Gérard Biau, Luc Devroye, Vida Dujmovic, Adam Krzyzak
2012	J	`jnl`	Analysis of a Random Forests Model. J. Mach. Learn. Res. Gérard Biau
2012	J	`jnl`	Parameter Selection for Principal Curves. IEEE Trans. Inf. Theory Gérard Biau, Aurélie Fischer
2011	J	`jnl`	Sequential Quantile Prediction of Time Series. IEEE Trans. Inf. Theory Gérard Biau, Benoît Patra
2010	J	`jnl`	On the Rate of Convergence of the Bagged Nearest Neighbor Estimate. J. Mach. Learn. Res. Gérard Biau, Frédéric Cérou, Arnaud Guyader
2010	J	`jnl`	On the layered nearest neighbour estimate, the bagged nearest neighbour estimate and the random forest method in regression and classification. J. Multivar. Anal. Gérard Biau, Luc Devroye
2010	J	`jnl`	Rates of convergence of the functional k-nearest neighbor estimate. IEEE Trans. Inf. Theory Gérard Biau, Frédéric Cérou, Arnaud Guyader
2008	J	`jnl`	Consistency of Random Forests and Other Averaging Classifiers. J. Mach. Learn. Res. Gérard Biau, Luc Devroye, Gábor Lugosi
2008	J	`jnl`	On the Performance of Clustering in Hilbert Spaces. IEEE Trans. Inf. Theory Gérard Biau, Luc Devroye, Gábor Lugosi
2008	J	`jnl`	Recovering probabilities for nucleotide trimming processes for T cell receptor TRA and TRG V-J junctions analyzed with IMGT tools. BMC Bioinform. Kevin Bleakley, Marie-Paule Lefranc, Gérard Biau
2007	—	`conf`	Supervised reconstruction of biological networks with local models. ISMB/ECCB (Supplement of Bioinformatics) Kevin Bleakley, Gérard Biau, Jean-Philippe Vert
2006	J	`jnl`	IMGT Standardization for Statistical Analyses of T Cell Receptor Junctions: The TRAV-TRAJ Example. Silico Biol. Kevin Bleakley, Véronique Giudicelli, Yan Wu, Marie-Paule Lefranc, Gérard Biau
2005	J	`jnl`	Functional classification in Hilbert spaces. IEEE Trans. Inf. Theory Gérard Biau, Florentina Bunea, Marten H. Wegkamp
2005	J	`jnl`	On the asymptotic properties of a nonparametric L IEEE Trans. Inf. Theory Gérard Biau, László Györfi
2004	J	`jnl`	A note on density model size testing. IEEE Trans. Inf. Theory Gérard Biau, Luc Devroye