DeepMass was developed for inferring dark matter maps from weak gravitational lensing measurements, and uses deep learning to reconstruct cosmological maps.
DeepMass can also be incorporated into a Moment Network (see ArXiv:2011.05991) enabling high-dimensional likelihood-free inference.
(Dark matter mass map demo DES_mass_maps_demo/Training_example)
CMB result from ``Single frequency CMB B-mode inference with realistic foregrounds from a single training image'' Jeffrey et al. 2021 MNRAS Letters
(CMB Foreground demo CMB_foreground_demo/MomentNetwork_foregrounds)
To download data associated with the demos, this repository uses Git Large File Storage (git-lfs): https://git-lfs.github.com/
If this is not installed locally, the downloaded repository will include code but not data.
!pip install 'git+https://github.com/NiallJeffrey/DeepMass.git'
python setup.py install
or for a cluster:
python setup.py install --user
Python 3; Tensorflow>=2.2; healpy
python unit_tests.py
- Niall Jeffrey
- Francois Lanusse
This project is licensed under the MIT License - see the LICENSE.md file for details