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"Graph Neural Rough Differential Equations for Traffic Forecasting", ACM TIST

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Graph Neural Rough Differential Equations for Traffic Forecasting

Setup Python environment for STG-NRDE

Install python environment

$ conda env create -f environment.yml 

Reproducibility

In terminal

  • Run the shell file (at the root of the project)
$ bash run_pemsd4.sh
  • Run the python file (at the model folder)
$ cd model

$ python Run.py --dataset='PEMSD4' --model='GRDE' --model_type='rde2' --embed_dim=10 --hid_dim=64 --hid_hid_dim=64 --num_layers=2 --lr_init=0.001 --weight_decay=1e-3 --epochs=200 --comment="" --input_dim=3 --depth=2 --wnd_len=2 --device=0 --tensorboard

Usage

PeMSD3

python Run.py --dataset='PEMSD3' --model='GRDE' --model_type='rde2' --embed_dim=5 --hid_dim=64 --hid_hid_dim=64 --num_layers=1 --lr_init=0.001 --weight_decay=2e-3 --epochs=200 --tensorboard --comment="" --input_dim=5 --depth=3 --wnd_len=2 --device=0

PeMSD4

python Run.py --dataset='PEMSD4' --model='GRDE' --model_type='rde2' --embed_dim=10 --hid_dim=64 --hid_hid_dim=64 --num_layers=2 --lr_init=0.001 --weight_decay=1e-3 --epochs=200 --comment="" --input_dim=3 --depth=2 --wnd_len=2 --device=0 --tensorboard

PeMSD7

python Run.py --dataset='PEMSD7' --model='GRDE' --model_type='rde2' --embed_dim=10 --hid_dim=64 --hid_hid_dim=64 --num_layers=1 --lr_init=0.001 --weight_decay=8e-4 --epochs=200 --comment="" --input_dim=3 --depth=2 --wnd_len=2 --device=0 --tensorboard

PeMSD8

python Run.py --dataset='PEMSD8' --model='GRDE' --model_type='rde2' --embed_dim=3 --hid_dim=32 --hid_hid_dim=256 --num_layers=1 --lr_init=8e-4 --weight_decay=2e-3 --epochs=200 --comment="" --input_dim=3 --depth=2 --wnd_len=2 --device=0 --tensorboard

PeMSD7(M)

python Run.py --dataset='PEMSD7M' --model='GRDE' --model_type='rde2' --embed_dim=10 --hid_dim=64 --hid_hid_dim=64 --num_layers=2 --lr_init=0.001 --weight_decay=1e-3 --epochs=200 --comment="" --input_dim=3 --depth=2 --wnd_len=2 --device=0 --tensorboard

PeMSD7(L)

python Run.py --dataset='PEMSD7L' --model='GRDE' --model_type='rde2' --embed_dim=10 --hid_dim=32 --hid_hid_dim=64 --num_layers=2 --lr_init=0.001 --weight_decay=1e-3 --epochs=200 --comment="" --input_dim=8 --depth=4 --wnd_len=2 --device=0 --tensorboard

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