2 papers
cs.LG2021
RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting
Nils Thoma, Zhongjie Yu, Fabrizio Ventola +1
Time series forecasting is a relevant task that is performed in several real-world scenarios such as product sales analysis and prediction of energy demand. Given their accuracy pe…
cs.AI2019
DeepAlign: Alignment-based Process Anomaly Correction using Recurrent Neural Networks
Timo Nolle, Alexander Seeliger, Nils Thoma +1
In this paper, we propose DeepAlign, a novel approach to multi-perspective process anomaly correction, based on recurrent neural networks and bidirectional beam search. At the core…