GAS-Norm: Score-Driven Adaptive Normalization for Non-Stationary Time Series Forecasting in Deep Learning.

Edoardo Urettini|Daniele Atzeni|Reshawn Ramjattan|Antonio Carta


Anthology ID:DBLP:conf/cikm/UrettiniARC24
Volume:Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024
Year:2024
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:2282-2291
URL:https://doi.org/10.1145/3627673.3679822
DOI:https://doi.org/10.1145/3627673.3679822
DBLP:conf/cikm/UrettiniARC24
BibTeX:
@inproceedings{urettini-2024-gasnorm, author = {Edoardo Urettini and Daniele Atzeni and Reshawn Ramjattan and Antonio Carta}, editor = {Edoardo Serra and Francesca Spezzano}, title = {{GAS-Norm: Score-Driven Adaptive Normalization for Non-Stationary Time Series Forecasting in Deep Learning}}, booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}}, pages = {2282--2291}, publisher = {ACM}, year = {2024}, url = {https://doi.org/10.1145/3627673.3679822}, doi = {https://doi.org/10.1145/3627673.3679822} }