Interpretable predictive modeling of non-stationary long time series
D Qin, Z Peng, L Wu - Computers & Industrial Engineering, 2024 - Elsevier
Highly accurate and interpretable forecasting of non-stationary long-time series is a
challenge. It is often difficult for existing models to capture the trends of non-stationary time …
challenge. It is often difficult for existing models to capture the trends of non-stationary time …
The Explainability of Transformers: Current Status and Directions
P Fantozzi, M Naldi - Computers, 2024 - mdpi.com
An increasing demand for model explainability has accompanied the widespread adoption
of transformers in various fields of applications. In this paper, we conduct a survey of the …
of transformers in various fields of applications. In this paper, we conduct a survey of the …
ChronoEpilogi: Scalable Time Series Selection with Multiple Solutions
E Vareille, M Linardi, I Tsamardinos… - The Thirty-eighth Annual … - openreview.net
We consider the problem of selecting all the minimal-size subsets of multivariate time-series
(TS) variables whose past leads to an optimal predictive model for the future (forecasting) of …
(TS) variables whose past leads to an optimal predictive model for the future (forecasting) of …