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Upload Graph-WaveNet model trained on METR-LA

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  1. README.md +68 -0
  2. config.json +17 -0
  3. metadata.json +11 -0
  4. model.pth +3 -0
README.md ADDED
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+ ---
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+ tags:
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+ - traffic-forecasting
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+ - time-series
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+ - graph-neural-network
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+ - graph-wavenet
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+ datasets:
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+ - metr-la
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+ ---
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+
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+ # Graph-WaveNet Model - METR-LA
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+
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+ Graph WaveNet for traffic speed forecasting, combining graph convolution with dilated causal convolution.
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+
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+ ## Model Description
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+
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+ This model uses a graph neural network architecture that combines:
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+ - Adaptive adjacency matrix learning
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+ - Spatial graph convolution for capturing spatial dependencies
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+ - Temporal convolution with dilated causal convolutions
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+ - Multi-scale temporal receptive field
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+
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+ ## Evaluation Metrics
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+
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+ - **Test MAE**: 9.9133
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+ - **Test MAPE**: inf
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+ - **Test RMSE**: 21.8977
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+
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+
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+ ## Dataset
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+
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+ **METR-LA**: Traffic speed data from highway sensors.
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+
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+ ## Usage
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+
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+ ```python
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+ from utils.gwnet import load_from_hub
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+
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+ # Load model from Hub
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+ model = load_from_hub("METR-LA")
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+
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+ # Get predictions
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+ import numpy as np
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+ x = np.random.randn(10, 12, 207, 2) # (batch, seq_len, nodes, features)
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+ predictions = model.predict(x)
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+ ```
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+
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+ ## Training
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+
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+ Model was trained using the Graph-WaveNet implementation with default hyperparameters.
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+
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+ ## Citation
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+
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+ If you use this model, please cite the original Graph WaveNet paper:
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+
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+ ```bibtex
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+ @inproceedings{wu2019graph,
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+ title={Graph WaveNet for Deep Spatial-Temporal Graph Modeling},
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+ author={Wu, Zonghan and Pan, Shirui and Long, Guodong and Jiang, Jing and Zhang, Chengqi},
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+ booktitle={Proceedings of the 28th International Joint Conference on Artificial Intelligence},
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+ pages={1907--1913},
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+ year={2019}
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+ }
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+ ```
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+
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+ ## License
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+
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+ This model checkpoint is released under the same license as the training code.
config.json ADDED
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+ {
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+ "num_nodes": 207,
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+ "seq_length": 12,
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+ "horizon": 12,
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+ "input_dim": 2,
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+ "output_dim": 1,
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+ "nhid": 32,
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+ "epochs": 100,
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+ "batch_size": 64,
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+ "learning_rate": 0.001,
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+ "weight_decay": 0.0001,
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+ "dropout": 0.3,
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+ "device": "cuda",
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+ "gcn_bool": true,
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+ "addaptadj": true,
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+ "adjtype": "doubletransition"
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+ }
metadata.json ADDED
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+ {
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+ "dataset": "METR-LA",
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+ "upload_date": "2025-11-09T15:16:28.728700",
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+ "metrics": {
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+ "Test MAE": 9.91329574584961,
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+ "Test MAPE": Infinity,
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+ "Test RMSE": 21.897747039794922
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+ },
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+ "framework": "PyTorch",
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+ "model_type": "Graph-WaveNet"
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+ }
model.pth ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:9f2f83990a91d83e1a7657b38bae00c15935c9ab68b0f5e979fc5b88f35e7089
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+ size 1275379