Deep representation learning for time series forecasting
Time series forecasting has critical applications across business and scien- tific domains, such as demand forecasting, capacity planning and management, and anomaly detection. Being able to predict the future yields immense value, allowing us to make downstream decisions with more confidence. Deep...
Saved in:
Main Author: | WOO, Gerald |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2024
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/etd_coll/650 https://ink.library.smu.edu.sg/context/etd_coll/article/1648/viewcontent/GPIS_AY2020_PhD_Woo_Jiale_Gerald.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Unified training of universal time series forecasting transformers
by: WOO, Gerald, et al.
Published: (2024) -
Learning deep time-index models for time series forecasting
by: WOO, Jiale Gerald, et al.
Published: (2023) -
CoST: contrastive learning of disentangled seasonal-trend representations for time series forecasting
by: WOO, Gerald, et al.
Published: (2022) -
Time-series representation learning via temporal and contextual contrasting
by: Eldele, Emadeldeen, et al.
Published: (2022) -
Self-supervised learning for time series analysis : Taxonomy, progress, and prospects
by: ZHANG Kexin,, et al.
Published: (2024)