3 papers
stat.ML2019
Copulas as High-Dimensional Generative Models: Vine Copula Autoencoders
Natasa Tagasovska, Damien Ackerer, Thibault Vatter
We introduce the vine copula autoencoder (VCAE), a flexible generative model for high-dimensional distributions built in a straightforward three-step procedure. First, an autoencod…
q-fin.PR2019
Deep Smoothing of the Implied Volatility Surface
Damien Ackerer, Natasa Tagasovska, Thibault Vatter
We present a neural network (NN) approach to fit and predict implied volatility surfaces (IVSs). Atypically to standard NN applications, financial industry practitioners use such m…
cs.LG2018
Generative Models for Simulating Mobility Trajectories
Vaibhav Kulkarni, Natasa Tagasovska, Thibault Vatter +1
Mobility datasets are fundamental for evaluating algorithms pertaining to geographic information systems and facilitating experimental reproducibility. But privacy implications res…