A comprehensive survey of deep learning for time series forecasting: architectural diversity and open challenges
Crossref DOI link: https://doi.org/10.1007/s10462-025-11223-9
Published Online: 2025-04-23
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Kim, Jongseon
Kim, Hyungjoon
Kim, HyunGi
Lee, Dongjun
Yoon, Sungroh
Text and Data Mining valid from 2025-04-23
Version of Record valid from 2025-04-23
Article History
Accepted: 4 April 2025
First Online: 23 April 2025
Declarations
:
: The authors declare no competing interests.