SRD
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Official pytorch implementation of Spatial Relation Decomposition method (AAAI 23)
SRD
This is the official PyTorch implementation of Spatial Relation Decomposition (SRD) method described in AAAI 23 paper Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling.
Requirements
pytables==3.7.0
tensorboard==2.10.0
numba==0.55.1
numpy==1.21.5
pandas==1.4.2
scikit_learn>=1.1.1
torch>=1.8.0
utilsd==0.0.15
You can install all requirements with pip install -r requirements.txt
Data
We offer a sample of Pems-bay in data/ folder, the full datasets can be downloaded from https://github.com/liyaguang/DCRNN and https://github.com/laiguokun/multivariate-time-series-data.
Run experiments
You can run SRD-GRU and SRD-TCN with the following commands.
python -m forecaster.entry.tsforecast config/srdgru.yml
python -m forecaster.entry.tsforecast config/srdtcn.yml