1 citations · 1 across the 3 of their papers we have counts for
5 papers
The geometry of the adapted Bures--Wasserstein space
Beatrice Acciaio, Daniel Bartl, Anne Grass +2
The adapted Bures--Wasserstein space consists of Gaussian processes endowed with the adapted Wasserstein distance. It can be viewed as the analogue of the classical Bures--Wasserst…
Nested Optimal Transport Distances
Ruben Bontorno, Songyan Hou
Simulating realistic financial time series is essential for stress testing, scenario generation, and decision-making under uncertainty. Despite advances in deep generative models,…
Estimating causal distances with non-causal ones
Beatrice Acciaio, Songyan Hou, Gudmund Pammer
The adapted Wasserstein () distance refines the classical Wasserstein () distance by incorporating the temporal structure of stochastic processes. This makes the -distan…
Entropic adapted Wasserstein distance on Gaussians
Beatrice Acciaio, Songyan Hou, Gudmund Pammer
The adapted Wasserstein distance is a metric for quantifying distributional uncertainty and assessing the sensitivity of stochastic optimization problems on time series data. A com…
Time-Causal VAE: Robust Financial Time Series Generator
Beatrice Acciaio, Stephan Eckstein, Songyan Hou
We build a time-causal variational autoencoder (TC-VAE) for robust generation of financial time series data. Our approach imposes a causality constraint on the encoder and decoder…