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[ascl:2211.007] mgcnn: Standard and modified gravity (MG) cosmological models classifier

mgcnn is a Convolutional Neural Network (CNN) architecture for classifying standard and modified gravity (MG) cosmological models based on the weak-lensing convergence maps they produce. It is implemented in Keras using TensorFlow as the backend. The code offers three options for the noise flag, which correspond to noise standard deviations, and additional options for the number of training iterations and epochs. Confusion matrices and evaluation metrics (loss function and validation accuracy) are saved as numpy arrays in the generated output/ directory after each iteration.

Code site:
http://www.cosmostat.org/software/mgcnn
Described in:
https://ui.adsabs.harvard.edu/abs/2019PhRvD.100b3508P
Bibcode:
2022ascl.soft11007P

Views: 920

ascl:2211.007
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