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Thibault Vatter
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VineCopula: Statistical inference of vine copulas
T Nagler, U Schepsmeier, J Stoeber, EC Brechmann, B Graeler, T Erhardt, ...
R package version 2 (0), 2019
235*2019
Generalized additive models for conditional dependence structures
T Vatter, V Chavez-Demoulin
Journal of Multivariate Analysis 141, 147-167, 2015
722015
rvinecopulib: High performance algorithms for vine copula modeling
T Nagler, T Vatter
R package version 3, 2021
66*2021
Generalized additive models for pair-copula constructions
T Vatter, T Nagler
Journal of Computational and Graphical Statistics 27 (4), 715-727, 2018
512018
Deep smoothing of the implied volatility surface
D Ackerer, N Tagasovska, T Vatter
Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2020
492020
Distinguishing Cause from Effect Using Quantiles: Bivariate Quantile Causal Discovery
N Tagasovska, V Chavez-Demoulin, T Vatter
International Conference on Machine Learning, 9311-9323, 2020
42*2020
Copulas as high-dimensional generative models: Vine copula autoencoders
N Tagasovska, D Ackerer, T Vatter
Advances in Neural Information Processing Systems 32 (NeurIPS 2019), 2019
412019
Generative models for simulating mobility trajectories
V Kulkarni, N Tagasovska, T Vatter, B Garbinato
Workshop on Modeling and Decision-Making in the Spatiotemporal Domain …, 2018
372018
Kde1d: Univariate kernel density estimation
T Nagler, T Vatter
R package version 1 (2), 6, 2019
262019
gamCopula: Generalized additive models for bivariate conditional dependence structures and vine copulas
T Vatter, T Nagler
R package, 0.0-4, 2017
162017
Solving estimating equations with copulas
T Nagler, T Vatter
Journal of the American Statistical Association 119 (546), 1168-1180, 2024
112024
Non-parametric estimation of intraday spot volatility: disentangling instantaneous trend and seasonality
T Vatter, HT Wu, V Chavez-Demoulin, B Yu
Econometrics 3 (4), 864-887, 2015
82015
kde1d: Univariate Kernel Density Estimation, 2018
T Nagler, T Vatter
R package version 0.2 1, 0
7
Generalized additive models for conditional copulas
V Chavez-Demoulin, T Vatter
J. Multivariate Anal 141, 147-167, 2015
62015
Marginalizable density models
D Gilboa, A Pakman, T Vatter
arXiv preprint arXiv:2106.04741, 2021
52021
Dependent defaults and losses with factor copula models
D Ackerer, T Vatter
Dependence Modeling 5 (1), 375-399, 2017
52017
Generalized Additive Modeling For Multivariate Distributions
T Vatter
Université de Lausanne, Faculté des hautes études commerciales, 2016
12016
pyvinecopulib
T Nagler, T Vatter
https://doi.org/10.5281/zenodo.4288292, 2021
2021
Simulating Copulas: Stochastic Models, Sampling Algorithms, and Applications: Jan-Frederik Mai, Matthias Scherer, with contributions by Claudia Czado, Elke Korn, Ralf Korn, and …
T Vatter
Journal of the American Statistical Association 115 (529), 481-482, 2020
2020
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Articles 1–19