Victor Panaretos

Q: What Schools Are Affiliated With Victor Panaretos

Victor Panaretos is affiliated with the following schools: University of California, Berkeley, École Polytechnique Fédérale de Lausanne

Victor Panaretos's AcademicInfluence.com Rankings

Victor Panaretos

Mathematics

#5975

World Rank

#8347

Historical Rank

Statistics

#636

World Rank

#720

Historical Rank

Measure Theory

#4597

World Rank

#5380

Historical Rank

mathematics Degrees

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Mathematics

Why Is Victor Panaretos Influential?

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According to Wikipedia, Victor Michael Panaretos is a Greek mathematical statistician. He is currently Professor and Director at the Institute of Mathematics of the École Polytechnique Fédérale de Lausanne , where he holds the chair of Mathematical Statistics.

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Victor Panaretos'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

Statistical Aspects of Wasserstein Distances (2018) (268)
Fourier analysis of stationary time series in function space (2013) (126)
Second-Order Comparison of Gaussian Random Functions and the Geometry of DNA Minicircles (2010) (101)
An Invitation to Statistics in Wasserstein Space (2020) (97)
Amplitude and phase variation of point processes (2016) (94)
Fréchet means and Procrustes analysis in Wasserstein space (2017) (91)
Cramér–Karhunen–Loève representation and harmonic principal component analysis of functional time series (2013) (72)
Dispersion operators and resistant second-order functional data analysis (2012) (65)
Procrustes Metrics on Covariance Operators and Optimal Transportation of Gaussian Processes (2018) (48)
Annual Review of Statistics and Its Application Statistical Aspects of Wasserstein Distances (2019) (39)
Principal Flows (2014) (27)
Functional data analysis by matrix completion (2016) (27)
On random tomography with unobservable projection angles (2009) (23)
Detecting and Localizing Differences in Functional Time Series Dynamics: A Case Study in Molecular Biophysics (2016) (22)
Statistical unfolding of elementary particle spectra: Empirical Bayes estimation and bias-corrected uncertainty quantification (2015) (21)
Methodology and Convergence Rates for Functional Time Series Regression (2016) (14)
Partially observed branching processes for stochastic epidemics (2007) (12)
Distribution-on-Distribution Regression via Optimal Transport Maps (2021) (12)
Functional registration and local variations: Identifiability, rank, and tuning (2017) (11)
Sparsely observed functional time series: estimation and prediction (2018) (11)
Regression with genuinely functional errors-in-covariates (2017) (10)
Asymptotic inference for partially observed branching processes (2011) (10)
The diffusion of Radon shape (2006) (10)
Nonparametric Construction of Multivariate Kernels (2012) (8)
Representation of Radon shape diffusions via hyperspherical Brownian motion (2008) (6)
Sparse approximations of protein structure from noisy random projections (2011) (6)
Functional lagged regression with sparse noisy observations (2019) (5)
Functional Data Analysis with Rough Sampled Paths? (2021) (4)
A Statistical Analysis of the European Soccer Champions League (2002) (4)
Spatiotemporal Covariance Estimation by Shifted Partial Tracing (2019) (4)
A Statistician’s View on Deconvolution and Unfolding (2011) (4)
Hybrid regularisation and the (in)admissibility of ridge regression in infinite dimensional Hilbert spaces (2019) (4)
Spectral Simulation of Functional Time Series (2020) (3)
Second-order inference for functional data with application to DNA minicircles (2011) (3)
Frequentist estimation of an epidemic’s spreading potential when observations are scarce (2014) (3)
CovNet: Covariance networks for functional data on multidimensional domains (2021) (3)
Functional estimation of anisotropic covariance and autocovariance operators on the sphere (2021) (3)
Principal Separable Component Analysis via the Partial Inner Product (2020) (3)
Empirical Bayes unfolding of elementary particle spectra at the Large Hadron Collider (2014) (3)
Separable expansions for covariance estimation via the partial inner product (2022) (2)
Statistics for Mathematicians: A Rigorous First Course (2016) (2)
Random Surface Covariance Estimation by Shifted Partial Tracing (2019) (2)
10plus2minus5plus36plus3minus3Functional Data Analysis by Matrix Completion* (2017) (1)
Point Estimation of Model Parameters (2016) (1)
Functional Data Analysis with Rough Sample Paths? (2021) (1)
Empirical evolution equations (2018) (1)
Minimax Rate for Optimal Transport Regression between Distributions (2022) (1)
Nonparametric Estimation of Covariance and Autocovariance Operators on the Sphere (2021) (1)
Confidence Intervals for Model Parameters (2016) (1)
Generalized Spatial Regression with Differential Penalization (2013) (1)
Testing for the rank of a covariance operator (2019) (1)
Hybrid Regularisation of Functional Linear Models (2016) (1)
The completion of covariance kernels (2021) (1)
FRÉCHET MEANS IN WASSERSTEIN SPACE : GRADIENT DESCENT AND PROCRUSTES ANALYSIS (2016) (1)
Optimal Transport (2020) (1)
On the rate of convergence for the autocorrelation operator in functional autoregression (2022) (1)
Transportation-Based Functional ANOVA and PCA for Covariance Operators (2022) (1)
Statistical Methodology and Theory for Functional and Topological Data (2020) (0)
Sampling from Probability Distributions (2016) (0)
Separable Expansions for Covariance Estimation (2020) (0)
Continuously Indexed Graphical Models (2023) (0)
Inference and Computation for Sparsely Sampled Random Surfaces (2021) (0)
Nonparametric Estimation for SDE with Sparsely Sampled Paths: an FDA Perspective (2021) (0)
A Karhunen-Lo\`{e}ve Theorem for Random Flows in Hilbert spaces (2023) (0)
Sparse Approximations of Protein Structure Given Noisy Random Projections (2009) (0)
Fréchet Means in the Wasserstein Space $$\mathcal W_2$$ (2020) (0)
Regular Probability Models (2016) (0)
Detecting Whether a Stochastic Process is Finitely Expressed in a Basis (2021) (0)
A Conversation with David R. Brillinger (2011) (0)
Phase Variation and Fréchet Means (2020) (0)
Construction of Fréchet Means and Multicouplings (2020) (0)
Nonparametric Kernels for Multivariate Density Estimation (2011) (0)
List of talks and abstracts : Workshop on high-dimensional Stochastics , WPI institute 7-9 September , 2020 (2020) (0)
The Wasserstein Space (2020) (0)
On Distributional Autoregression and Iterated Transportation (2023) (0)
Noise-resistant tomographic reconstruction under unknown angles (2018) (0)
Foreword (2020) (0)
Separation of Amplitude and Phase Variation in Point Processes (2014) (0)
Estimating the Spreading Potential of an Epidemic When Observations Are Scarce (2012) (0)
Tests of Hypotheses for Model Parameters (2016) (0)

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Other Resources About Victor Panaretos

What Schools Are Affiliated With Victor Panaretos?

Victor Panaretos is affiliated with the following schools:

Victor Panaretos's Academic­Influence.com Rankings

Why Is Victor Panaretos Influential?

Victor Panaretos's Published Works

Published Works

Other Resources About Victor Panaretos

What Schools Are Affiliated With Victor Panaretos?

Victor Panaretos's AcademicInfluence.com Rankings