Olivier Zahm | Academic Influence

Olivier Zahm's AcademicInfluence.com Rankings

Olivier Zahm

Communications

#1916

World Rank

#2800

Historical Rank

Journalism

#1084

World Rank

#1259

Historical Rank

communications Degrees

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Communications

Why Is Olivier Zahm Influential?

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According to Wikipedia, Olivier Zahm is a French magazine editor, art critic, art director, curator, writer, and photographer He is the co-founder, owner, and current editor-in-chief of the bi-annual art and fashion magazine Purple. In addition to his innovative print publishing, he is a recognized pioneering cultural influence at the dawn of the electronic era during the Digital Revolution. His early blogs garnered notoriety, and featured highly stylized photographs taken by him, that took his audience on daily tours of his fantasyland populated by the artists, intellectuals, designers, filmmakers, socialites, models and celebrities who regularly appeared in his magazine. His aesthetic has been described as anti-fashion, counterculture, and unfettered by the constraints of the mainstream publishing world. His online activity served as an early electronic precursor to popular social media platforms like Facebook and Instagram. His magazine remains one of the only independent and privately owned publications of its kind. Created in the beginning of the 1990s – it still remains a major reference for other alternative magazines today.

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Olivier Zahm's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Gradient-Based Dimension Reduction of Multivariate Vector-Valued Functions (2018) (48)
Certified dimension reduction in nonlinear Bayesian inverse problems (2018) (43)
A tensor approximation method based on ideal minimal residual formulations for the solution of high-dimensional problems ∗ (2013) (43)
Shared low-dimensional subspaces for propagating kinetic uncertainty to multiple outputs (2018) (35)
Multifidelity Dimension Reduction via Active Subspaces (2018) (33)
Interpolation of Inverse Operators for Preconditioning Parameter-Dependent Equations (2015) (31)
Greedy inference with structure-exploiting lazy maps (2019) (28)
Randomized Residual-Based Error Estimators for Parametrized Equations (2018) (16)
An adaptive transport framework for joint and conditional density estimation (2020) (16)
Greedy inference with layers of lazy maps (2019) (13)
On the representation and learning of monotone triangular transport maps (2020) (12)
Data-free likelihood-informed dimension reduction of Bayesian inverse problems (2021) (10)
A fast boundary element method for the solution of periodic many-inclusion problems via hierarchical matrix techniques (2015) (10)
Nonlinear dimension reduction for surrogate modeling using gradient information (2021) (10)
Randomized residual‐based error estimators for the proper generalized decomposition approximation of parametrized problems (2019) (10)
Learning non-Gaussian graphical models via Hessian scores and triangular transport (2021) (9)
Projection-Based Model Order Reduction Methods for the Estimation of Vector-Valued Variables of Interest (2016) (5)
Gradient-based data and parameter dimension reduction for Bayesian models: an information theoretic perspective (2022) (4)
Conditional Deep Inverse Rosenblatt Transports (2021) (4)
Model order reduction methods for parameter-dependent equations -- Applications in Uncertainty Quantification. (2015) (2)
Minimizing Rational Functions: A Hierarchy of Approximations via Pushforward Measures (2020) (1)
Prior normalization for certified likelihood-informed subspace detection of Bayesian inverse problems (2022) (1)
GOAL-ORIENTED LOW-RANK APPROXIMATIONS FOR HIGH DIMENSIONAL STOCHASTIC PROBLEMS (2013) (1)
APPLICATION OF HIERARCHICAL MATRIX TECHNIQUES TO THE HOMOGENIZATION OF COMPOSITE MATERIALS (2013) (1)
Self-reinforced polynomial approximation methods for concentrated probability densities (2023) (1)
Scalable Conditional Deep Inverse Rosenblatt Transports Using Tensor-Trains and Gradient-Based Dimension Reduction (2021) (1)
Ph.D. offer in applied mathematics: Adaptive sampling strategy for nonlinear dimension reduction in uncertainty quantification (2022) (0)
Constant-Free, Randomized a Posteriori Error Estimators for Parameter-Dependent Partial Differential Equations (2018) (0)
Certified dimension reduction of the input parameter space of multivariate functions (2018) (0)
No, Not That One It's Not a Chair (1990) (0)
Certified dimension reduction of the input parameter space of vector-valued functions (2018) (0)
Tensor-based methods for uncertainty propagation: alternative definitions and algorithms (2012) (0)
Detecting and exploiting the low-effective dimension of multivariate problems using gradient information (2018) (0)
A Tensor-Based Algorithm for the Optimal Model Reduction of High Dimensional Problems (2013) (0)
Projection-based Model Order Reduction techniques (2018) (0)
Dimension reduction of the input parameter space of vector-valued functions (2018) (0)
Définition, situation, expiration : Lionel Fourneaux, Wendy Jacob, Hervé Leforestier, Mindy Yan Miller (1995) (0)
Interpolation of the inverse of parameter dependent operator for preconditioning parametric and stochastic equations (2015) (0)
Certified dimension reduction of the input parameter space of Bayesian inverse problems (2018) (0)

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Other Resources About Olivier Zahm

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What Schools Are Affiliated With Olivier Zahm?

Olivier Zahm is affiliated with the following schools:

Grenoble Institute of Technology

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