TACTiS: Transformer-Attentional Copulas for Time Series. (arXiv:2202.03528v2 [cs.LG] UPDATED)

The estimation of time-varying quantities is a fundamental component of
decision making in fields such as healthcare and finance. However, the
practical utility of such estimates is limited by how accurately they quantify
predictive uncertainty. In this work, we address the problem of estimating the
joint predictive distribution of high-dimensional multivariate time series. We
propose a versatile method, based on the transformer architecture, that
estimates joint distributions using an attention-based decoder that provably
learns to mimic the properties of non-parametric …

arxiv lg series time time series transformer