lusccc/stnn

Code for the paper "Spatio-Temporal Neural Networks for Space-Time Series Modeling and Relations Discovery"

Spatio-Temporal Neural Networks for Space-Time Series Forecasting and Relation Discovery

ICDM 2018 - IEEE International Conference on Data Mining series (ICDM)

Paper

Commands for reproducing synthetic experiments:

Heat Diffusion

STNN

python train_stnn.py --dataset heat --outputdir output_heat --manualSeed 2021 --xp stnn

STNN-R(efine)

python train_stnn.py --dataset heat --outputdir output_heat --manualSeed 5718 --xp stnn_r --mode refine --patience 800 --l1_rel 1e-8

STNN-D(iscovery)

python train_stnn.py --dataset heat --outputdir output_heat --manualSeed 9690 --xp stnn_d --mode discover --patience 1000 --l1_rel 3e-6

Modulated Heat Diffusion

STNN

python train_stnn.py --dataset heat_m --outputdir output_heat_m --manualSeed 679 --xp stnn

STNN-R(efine)

python train_stnn.py --dataset heat_m --outputdir output_heat_m --manualSeed 3488 --xp stnn_r --mode refine --l1_rel 1e-5

STNN-D(iscovery)

python train_stnn_.py --dataset heat_m --outputdir output_m --xp test --manualSeed 7664 --mode discover --patience 500 --l1_rel 3e-6