Probabilistic time series forecasting with deep non‐linear state space models-Reference-Cited by-同舟云学术

Probabilistic time series forecasting with deep non‐linear state space models

Published:2022-04 Issue:1 Volume:8 Page:3-13
ISSN:2468-2322
Container-title:CAAI Transactions on Intelligence Technology
language:en
Short-container-title:CAAI Trans on Intel Tech

Author:

Du Heming¹^ORCID,Du Shouguo²^ORCID,Li Wen³

Affiliation:

1. School of Computer Science, College of Engineering and Computer Science Australian National University Canberra Australian Capital Territory Australia

2. Shanghai Municipal Big Data Center Shanghai China

3. Department of Economic Statistics, School of Statistics and Information Shanghai University of International Business and Economics Shanghai China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Vision and Pattern Recognition,Human-Computer Interaction,Information Systems

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/cit2.12085

Reference45 articles.

1. Time-Series Forecasting

2. Time Series Analysis by State Space Methods

3. Rangapuram S.S. et al.:Deep state space models for time series forecasting. In: Advances in neural information processing system vol. 31 pp.7785–7794(2018)

4. Unscented Filtering and Nonlinear Estimation

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