GitHub topics: time-series-representation-learning
PaddlePaddle/PaddleTS
Awesome Easy-to-Use Deep Time Series Modeling based on PaddlePaddle, including comprehensive functionality modules like TSDataset, Analysis, Transform, Models, AutoTS, and Ensemble, etc., supporting versatile tasks like time series forecasting, representation learning, and anomaly detection, etc., featured with quick tracking of SOTA deep models.
Language: Python - Size: 7.06 MB - Last synced at: 9 days ago - Pushed at: about 2 months ago - Stars: 517 - Forks: 123
OnurVural/contrex
CONTREX, a novel contrastive representation learning approach for multivariate time series data.
Language: Jupyter Notebook - Size: 1.02 MB - Last synced at: 7 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0
OnurVural/centroid_contrastive_learning
Introducing a novel centroid-based contrastive learning framework tailored specifically for time series data to address the challenges posed by temporal dependencies and extreme class imbalance in SWAN-SF dataset for solar flare classification.
Language: Jupyter Notebook - Size: 1.08 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0
aptx1231/CoST_Paddle
A PaddlePaddle implementation of CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting.
Language: Python - Size: 3.66 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 1
