PyTorch Implementation of: VPNets: Volume-preserving neural networks for learning source-free dynamics

Requirements

• Python
• torch
• numpy
• matplotlib

Reproducing the results of the paper

In general all parameters which need to be specified are given in the paper.

Running Experiments Volterra equations:

To train the models, run:

python LV.py --filename 'lv-l1' ----net_type 'LA'
python LV.py --filename 'lv-g1' ----net_type 'G'

After training, run:

python LV_output.py

on CPU

Running Experiments Charged particle dynamics:

Here, we used 5 different seed which can also be set via the command line random_seed parameter. To train the models, run:

python LF.py --filename 'lf-l'   --lr 0.01 --iterations 800000 
python LF.py --filename 'lf-g'   --lr 0.001 --iterations 500000 

After training, run:

python LF_output.py

on CPU

References

[1] learner