awesome-time-series
github.com/cure-lab/awesome-time-series ↗A comprehensive survey on the time series domains
549
GitHub Stars
242
Curated Resources
7
Categories
22 hours ago
Last Refreshed
SurveyTime Series ForecastingTime Series ClassificationAnomaly DetectionTime series ClusteringTime series SegmentationOthers
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me time series forecasting resources from awesome-time-series"
Installation instructions →What's inside
Time Series Forecasting
- Actionable Insights in Urban Multivariate Time-series
CIKM
- AdaRNN: Adaptive Learning and Forecasting of Time Series
CIKM
- Adversarial Sparse Transformer for Time Series Forecasting
NeurIPS
- AGCNT: Adaptive Graph Convolutional Network for Transformer-based Long Sequence Time-Series Forecasting
CIKM
- A GNN-RNN Approach for Harnessing Geospatial and Temporal Information: Application to Crop Yield Prediction
AAAI
- A PLAN for Tackling the Locust Crisis in East Africa: Harnessing Spatiotemporal Deep Models for Locust Movement Forecasting
KDD
Others
- Adaptive Conformal Predictions for Time Series
ICML
- Adjusting for Autocorrelated Errors in Neural Networks for Time Series
NeurIPS
- A Graph Temporal Information Learning Framework for Popularity Prediction
WWW
- ARMA Nets: Expanding Receptive Field for Dense Prediction
NeurIPS
- CASPITA: Mining Statistically Significant Paths in Time Series Data from an Unknown Network
ICDM
- Conditional Loss and Deep Euler Scheme for Time Series Generation
AAAI
Survey
- An empirical survey of data augmentation for time series classification with neural networks
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- Applications of deep learning in stock market prediction: Recent progress
ESA
- A review on outlier/anomaly detection in time series data
ACM Computing Surveys
- A unifying review of deep and shallow anomaly detection
Proceedings of the IEEE
- Big Data for Traffic Estimation and Prediction: A Survey of Data and Tools
Applied System Innovation 5
- Deep learning for anomaly detection in time-series data: review, analysis, and guidelines
Access
Anomaly Detection
- Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy
ICLR
- Application Performance Anomaly Detection with LSTM on Temporal Irregularities in Logs
CIKM
- A Semi-Supervised VAE Based Active Anomaly Detection Framework in Multivariate Time Series for Online Systems
WWW
- BiCMTS: Bidirectional Coupled Multivariate Learning of Irregular Time Series with Missing Values
CIKM
- Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation
NeurIPS
- DeepGPD: A Deep Learning Approach for Modeling Geospatio-Temporal Extreme Events
AAAI
Time Series Classification
- Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting
ICDM
- Contrast Profile: A Novel Time Series Primitive that Allows Classification in Real World Settings
ICDM
- Correlative Channel-Aware Fusion for Multi-View Time Series Classification
AAAI
- Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns To Attend To Important Variables As Well As Time Intervals
WSDM
- Fast and Accurate Time Series Classification Through Supervised Interval Search
CIKM
- Gaussian Process Model Learning for Time Series Classification
ICDM
Time series Segmentation
Showing a sample of 242 resources. View the full list on GitHub →