Marius Hofert

31 papers A* 1Journal 28Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
Adaptive generative moment matching networks for improved learning of dependence structures.
CoRR
Marius Hofert, Gan Yao
2024 J jnl
Comparison of correlation-based measures of concordance in terms of asymptotic variance.
J. Multivar. Anal.
Takaaki Koike, Marius Hofert
2024 — conf
Implicit and Explicit Policy Constraints for Offline Reinforcement Learning.
CLeaR
Yang Liu, Marius Hofert
2024 A* conf
Policy Optimization by Looking Ahead for Model-based Offline Reinforcement Learning.
ICRA
Yang Liu, Marius Hofert
2023 J jnl
Dependence Model Assessment and Selection with DecoupleNets.
J. Comput. Graph. Stat.
Marius Hofert, Avinash Prasad, Mu Zhu
2022 J jnl
Dependence model assessment and selection with DecoupleNets.
CoRR
Marius Hofert, Avinash Prasad, Mu Zhu
2022 J jnl
Multivariate Normal Variance Mixtures in
J. Stat. Softw.
Erik Hintz, Marius Hofert, Christiane Lemieux
2021 J jnl
Normal variance mixtures: Distribution, density and parameter estimation.
Comput. Stat. Data Anal.
Erik Hintz, Marius Hofert, Christiane Lemieux
2021 J jnl
Outer power transformations of hierarchical Archimedean copulas: Construction, sampling and estimation.
Comput. Stat. Data Anal.
Jan Górecki, Marius Hofert, Ostap Okhrin
2021 J jnl
Quasi-Random Sampling for Multivariate Distributions via Generative Neural Networks.
J. Comput. Graph. Stat.
Marius Hofert, Avinash Prasad, Mu Zhu
2021 J jnl
RafterNet: Probabilistic predictions in multi-response regression.
CoRR
Marius Hofert, Avinash Prasad, Mu Zhu
2020 — conf
Applications of Multivariate Quasi-Random Sampling with Neural Networks.
MCQMC
Marius Hofert, Avinash Prasad, Mu Zhu
2020 J jnl
Applications of multivariate quasi-random sampling with neural networks.
CoRR
Marius Hofert, Avinash Prasad, Mu Zhu
2020 J jnl
Multivariate time-series modeling with generative neural networks.
CoRR
Marius Hofert, Avinash Prasad, Mu Zhu
2020 J jnl
Random number generators produce ties: Why and how many.
CoRR
Marius Hofert
2020 J jnl
Zigzag Expanded Navigation Plots in R: The R Package zenplots.
J. Stat. Softw.
Marius Hofert, Wayne Oldford
2019 J jnl
A framework for measuring association of random vectors via collapsed random variables.
J. Multivar. Anal.
Marius Hofert, Wayne Oldford, Avinash Prasad, Mu Zhu
2018 J jnl
Hierarchical Archimax copulas.
J. Multivar. Anal.
Marius Hofert, Raphaël Huser, Avinash Prasad
2018 J jnl
Quasi-random number generators for multivariate distributions based on generative neural networks.
CoRR
Marius Hofert, Avinash Prasad, Mu Zhu
2017 J jnl
Quasi-random numbers for copula models.
Stat. Comput.
Mathieu Cambou, Marius Hofert, Christiane Lemieux
2016 J jnl
An approach to structure determination and estimation of hierarchical Archimedean Copulas and its application to Bayesian classification.
J. Intell. Inf. Syst.
Jan Górecki, Marius Hofert, Martin Holena
2015 J jnl
Construction and sampling of Archimedean and nested Archimedean Lévy copulas.
J. Multivar. Anal.
Oliver Grothe, Marius Hofert
2013 J jnl
A note on generalized inverses.
Math. Methods Oper. Res.
Paul Embrechts, Marius Hofert
2013 J jnl
Densities of nested Archimedean copulas.
J. Multivar. Anal.
Marius Hofert, David Pham
2013 J jnl
On Sampling from the Multivariate t Distribution.
R J.
Marius Hofert
2013 J jnl
Sibuya copulas.
J. Multivar. Anal.
Marius Hofert, Frédéric Vrins
2012 J jnl
Likelihood inference for Archimedean copulas in high dimensions under known margins.
J. Multivar. Anal.
Marius Hofert, Martin Mächler, Alexander J. McNeil
2011 J jnl
Efficiently sampling nested Archimedean copulas.
Comput. Stat. Data Anal.
Marius Hofert
2011 J jnl
Sampling Exponentially Tilted Stable Distributions.
ACM Trans. Model. Comput. Simul.
Marius Hofert
2010 J jnl
Constructing hierarchical Archimedean copulas with Lévy subordinators.
J. Multivar. Anal.
Christian Hering, Marius Hofert, Jan-Frederik Mai, Matthias Scherer
2008 J jnl
Sampling Archimedean copulas.
Comput. Stat. Data Anal.
Marius Hofert