267 citations · 286 across the 12 of their papers we have counts for
5 papers · 1 filter
Sig-Splines: universal approximation and convex calibration of time series generative models
Magnus Wiese, Phillip Murray, Ralf Korn
We propose a novel generative model for multivariate discrete-time time series data. Drawing inspiration from the construction of neural spline flows, our algorithm incorporates li…
Estimating the Value-at-Risk by Temporal VAE
Robert Sicks, Stefanie Grimm, Ralf Korn +1
Estimation of the value-at-risk (VaR) of a large portfolio of assets is an important task for financial institutions. As the joint log-returns of asset prices can often be projecte…
A Generalised Linear Model Framework for -Variational Autoencoders based on Exponential Dispersion Families
Robert Sicks, Ralf Korn, Stefanie Schwaar
Although variational autoencoders (VAE) are successfully used to obtain meaningful low-dimensional representations for high-dimensional data, the characterization of critical point…
A lower bound for the ELBO of the Bernoulli Variational Autoencoder
Robert Sicks, Ralf Korn, Stefanie Schwaar
We consider a variational autoencoder (VAE) for binary data. Our main innovations are an interpretable lower bound for its training objective, a modified initialization and archite…
Copula & Marginal Flows: Disentangling the Marginal from its Joint
Magnus Wiese, Robert Knobloch, Ralf Korn
Deep generative networks such as GANs and normalizing flows flourish in the context of high-dimensional tasks such as image generation. However, so far exact modeling or extrapolat…