Making Time Series Embeddings More Interpretable in Deep Learning
With the success of language models in deep learning, multiple new time series embeddings have been proposed. However, the interpretability of those representations is often still lacking compared to word embeddings. This paper tackles this issue, aiming to present some criteria for making time seri...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
LibraryPress@UF
2023-05-01
|
| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Subjects: | |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/133107 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|