Benoit Oriol

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All published works

Action	Title	Year	Authors
+	WeSpeR: Population spectrum retrieval and spectral density estimation of weighted sample covariance	2024	Benoit Oriol
+	Asymptotic spectrum of weighted sample covariance: a Marcenko-Pastur generalization	2024	Benoit Oriol
+	Asymptotic non-linear shrinkage formulas for weighted sample covariance	2024	Benoit Oriol
+ PDF Chat	Analysis of a multi-target linear shrinkage covariance estimator	2024	Benoit Oriol
+	Ledoit-Wolf linear shrinkage with unknown mean	2023	Benoit Oriol Alexandre Miot
+	On some theoretical limitations of Generative Adversarial Networks	2021	Benoit Oriol Alexandre Miot

Common Coauthors

Coauthor	Papers Together
Alexandre Miot	2

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Comparison of linear shrinkage estimators of a large covariance matrix in normal and non-normal distributions	2015	Yuki Ikeda Tatsuya Kubokawa Muni S. Srivastava	1
+	The Brunn-Minkowski inequality in Gauss space	1975	Christer Borell	1
+ PDF Chat	Extremal properties of half-spaces for spherically invariant measures	1978	V. N. Sudakov Boris Tsirelson	1
+ PDF Chat	Residual Life Time at Great Age	1974	A. A. Balkema Laurens de Haan	1
+ PDF Chat	An isoperimetric inequality on the discrete cube, and an elementary proof of the isoperimetric inequality in Gauss space	1997	Sergey G. Bobkov	1
+ PDF Chat	A well-conditioned estimator for large-dimensional covariance matrices	2003	Olivier Ledoit Michael Wolf	1
+ PDF Chat	Shrinkage Algorithms for MMSE Covariance Estimation	2010	Yilun Chen Ami Wiesel Yonina C. Eldar Alfred O. Hero	1
+	G2-estimator for the Stieltjes Transform of the Normalized Spectral Function of Covariance Matrices	1995	Vyacheslav L. Girko	1
+ PDF Chat	G-analysis of high-dimensional observations	1992	Vyacheslav L. Girko	1
+	Lectures on Lipschitz analysis	2005	Juha Heinonen	1
+	Understanding the exploding gradient problem	2012	Razvan Pascanu Tomáš Mikolov Yoshua Bengio	1
+ PDF Chat	A theoretical study of Stein's covariance estimator	2016	Bala Rajaratnam Dario Vincenzi	1
+	Linear shrinkage estimation of large covariance matrices using factor models	2016	Yuki Ikeda Tatsuya Kubokawa	1
+	High-Dimensional Probability: An Introduction with Applications in Data Science	2018	Roman Vershynin	1
+ PDF Chat	Analytical nonlinear shrinkage of large-dimensional covariance matrices	2020	Olivier Ledoit Michael Wolf	1
+	Nonlinear shrinkage estimation of large-dimensional covariance matrices	2012	Olivier Ledoit Michael Wolf	1
+	Large Dimensional Analysis and Optimization of Robust Shrinkage Covariance Matrix Estimators	2014	Romain Couillet Matthew R. McKay	1
+	Copula & Marginal Flows: Disentangling the Marginal from its Joint	2019	Magnus Wiese Robert Knobloch Ralf Korn	1
+ PDF Chat	Optimal shrinkage for robust covariance matrix estimators in a small sample size setting	2021	Karina Ashurbekova Antoine Usseglio‐Carleve Florence Forbes Sophie Achard	1
+ PDF Chat	Nonlinear 3D cosmic web simulation with heavy-tailed generative adversarial networks	2020	Richard M. Feder Philippe Berger George Stein	1
+ PDF Chat	Optimal estimation of a large-dimensional covariance matrix under Stein’s loss	2018	Olivier Ledoit Michael Wolf	1
+	Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions	2021	Todd Huster Jérémy E. Cohen Zinan Lin Kevin Chan Charles Kamhoua Nandi Leslie Cho‐Yu Jason Chiang Vyas Sekar	1
+	Estimation of a covariance matrix	1975	C. Stein	1
+ PDF Chat	Approximation by superpositions of a sigmoidal function	1992	George Cybenko	1
+	Adversarial vulnerability for any classifier	2018	Alhussein Fawzi Hamza Fawzi Omar Fawzi	1
+	Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures	2020	Mohamed El Amine Seddik Cosme Louart Mohamed Tamaazousti Romain Couillet	1