itouchz/awesome-deep-time-series-representations
A curated list of state-of-the-art papers on deep learning for universal representations of time series.
For researchers and practitioners working with time-series data, this resource compiles state-of-the-art academic papers on using deep learning to create universal representations. It provides a curated list of research, categorized by architectural, learning, and data-centric approaches, along with related surveys. The primary user is a research scientist, data scientist, or academic exploring advanced methods for analyzing complex time-series datasets.
206 stars. No commits in the last 6 months.
Use this if you are a researcher or advanced data practitioner looking for academic literature on deep learning techniques for robust time-series feature extraction and representation.
Not ideal if you are looking for ready-to-use code, tutorials, or a high-level overview of time-series analysis for immediate application in business.
Stars
206
Forks
22
Language
—
License
MIT
Category
Last pushed
Jun 28, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/itouchz/awesome-deep-time-series-representations"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
sktime/sktime
A unified framework for machine learning with time series
aeon-toolkit/aeon
A toolkit for time series machine learning and deep learning
Nixtla/neuralforecast
Scalable and user friendly neural :brain: forecasting algorithms.
tslearn-team/tslearn
The machine learning toolkit for time series analysis in Python
Nixtla/mlforecast
Scalable machine 🤖 learning for time series forecasting.