ML-Mat-VAMP (Multi-layer - Matrix - VAMP)

Code to reproduce results from Matrix Inference and Estimation in Multi-Layer Models, NeurIPS 2020.

@article{pandit2020matrix,
  title={Matrix Inference and Estimation in Multi-Layer Models},
  author={Pandit, Parthe and Sahraee Ardakan, Mojtaba and Rangan, Sundeep and Schniter, Philip and Fletcher, Alyson K},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  year={2020}
}

Dependencies

tensorflow >= 2.3.1
scikit-learn
matplotlib

Plot results using stored data from our simulations

The following command will generate 2 subplots (Fig. 2 from the paper) and save them in mse_vs_ntr.png

python plot.py

Run your own experiments to plot results

To run multiple experiments:

python diy_expts/2layer_ALGO.py --act relu --snr 10.0 --fn_suffix k

for k = 0,1,..K-1.
The above command creates the file adam_snr10_k.pkl
By default k=0.
ALGO can be 'adam' or 'ml-mat-vamp'

Run experiments for Adam. This uses Keras

The following creates files adam_snr10_0.pkl and adam_snr15_0.pkl

python diy_expts/2layer_adam.py --act relu --snr 10.0
python diy_expts/2layer_adam.py --act relu --snr 15.0

Run experiments for ML-Mat-VAMP

python diy_expts/2layer_ml-mat-vamp.py --act relu --snr 10.0
python diy_expts/2layer_ml-mat-vamp.py --act relu --snr 15.0

Run experiments for State Evolution of ML-Mat-VAMP

python diy_expts/2layer_ml-mat-vamp.py --se_test --act relu --snr 10.0
python diy_expts/2layer_ml-mat-vamp.py --se_test --act relu --snr 15.0