Maximum-entropy tomography (MENT) using normalizing flows. Corresponding preprint: https://arxiv.org/abs/2406.00236.
git clone https://github.com/austin-hoover/ment-flow.git
cd ment-flow
pip install -e .
Experiments use hydra. Config files can be found in /experiments/config
. Parameters can be overridden with command line arguments. For example:
cd experiments/rec_2d/linear
python train_flow.py device=mps dist.name=swissroll meas.num=7
Results are stored in ./outputs/{script_name}/{timestamp}/
directory created in the working directory, so it's best to cd
to the script directory before running. Runtime parameters are stored in ./outputs/{script_name}/{timestamp}/config/
.