zhengdaoli / AGC-netLinks
AGC-Net (Adaptive Graph Convolution Networks) is an advanced model designed to predict traffic flow. Dataset: METR-LA, PEMS-BAY
☆11Updated 2 years ago
Alternatives and similar repositories for AGC-net
Users that are interested in AGC-net are comparing it to the libraries listed below
Sorting:
- [TITS2025] Pattern-Matching Dynamic Memory Network for Dual-Mode Traffic Prediction☆26Updated last month
- Display of data sets and core code in STCGCN☆26Updated 2 years ago
- Spatial–Temporal Dynamic Graph Convolutional Network With Interactive Learning for Traffic Forecasting☆73Updated 4 months ago
- ☆15Updated 2 years ago
- [Pattern Recognition] Decomposition Dynamic Graph Conolutional Recurrent Network for Traffic Forecasting☆88Updated last month
- ☆39Updated 2 years ago
- [KDD'24] Official code for our paper "Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting".☆64Updated last year
- [ICDE'2023] When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks☆101Updated 6 months ago
- Code of “Dynamic Graph Convolutional Network with Attention Fusion for Traffic Flow Prediction”.☆19Updated last year
- [IJCAI'2022] FOGS: First-Order Gradient Supervision with Learning-based Graph for Traffic Flow Forecasting☆27Updated 2 years ago
- source codes of TASSGN☆11Updated last year
- ☆14Updated 2 years ago
- ☆18Updated 2 years ago
- [SIGKDD'2025] Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective☆59Updated 2 months ago
- ☆27Updated last month
- A correlation information-based spatiotemporal network for traffic flow forecasting☆28Updated last year
- Time Series Forecasting with Dynamic Graph Modeling☆14Updated last month
- This is an implementation of a traffic speed predicition model.☆10Updated 2 years ago
- Dual Dynamic Spatial-Temporal Graph Convolution Network for Traffic Prediction☆49Updated 2 years ago
- ☆14Updated 3 years ago
- The code for Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values.☆28Updated last year
- [Neural Networks] PDG2Seq: Periodic Dynamic Graph to Sequence model for Traffic Flow Prediction☆18Updated last month
- ☆11Updated 11 months ago
- SPGCL: Mining Spatio-Temporal Relations via Self-Paced Graph Contrastive Learning☆14Updated 2 years ago
- The pytorch implementation of ST-GRAT: A Novel Spatio-temporal Graph Attention Network for Accurately Forecasting Dynamically Changing Ro…☆42Updated 4 years ago
- ☆44Updated 3 years ago
- A pytorch re-implementation of STFGNN☆29Updated 2 years ago
- ☆10Updated 9 months ago
- ☆26Updated last year
- ☆27Updated 2 years ago