270 citations · 278 across the 5 of their papers we have counts for
5 papers
Mol-CycleGAN - a generative model for molecular optimization
Łukasz Maziarka, Agnieszka Pocha, Jan Kaczmarczyk +2
Designing a molecule with desired properties is one of the biggest challenges in drug development, as it requires optimization of chemical compound structures with respect to many…
Inference on the tail process with application to financial time series modelling
R. A. Davis, H. Drees, J. Segers +1
To draw inference on serial extremal dependence within heavy-tailed Markov chains, Drees, Segers and Warchoł [Extremes (2015) 18, 369--402] proposed nonparametric estimators of the…
Nonparametric estimation of extremal dependence
Anna Kiriliouk, Johan Segers, Michal Warchol
There is an increasing interest to understand the dependence structure of a random vector not only in the center of its distribution but also in the tails. Extreme-value theory tac…
Statistics for Tail Processes of Markov Chains
Holger Drees, Johan Segers, Michał Warchoł
At high levels, the asymptotic distribution of a stationary, regularly varying Markov chain is conveniently given by its tail process. The latter takes the form of a geometric rand…
A Euclidean likelihood estimator for bivariate tail dependence
Miguel de Carvalho, Boris Oumow, Johan Segers +1
The spectral measure plays a key role in the statistical modeling of multivariate extremes. Estimation of the spectral measure is a complex issue, given the need to obey a certain…