AntoineH/smart_augmentation: 'Smart_aug' objective is to make data augmentation differentiable, thus allowing to learn its parameters, with 'Higher' objects, such as 'Data_aug' classes. The meta-learning of the data augmentation parameter is performed jointly with the training of the model. Thus it minimize the overhead compared to other data augmentation learning techniques.

mirror of https://github.com/AntoineHX/smart_augmentation.git synced 2025-05-04 12:10:45 +02:00

'Smart_aug' objective is to make data augmentation differentiable, thus allowing to learn its parameters, with 'Higher' objects, such as 'Data_aug' classes. The meta-learning of the data augmentation parameter is performed jointly with the training of the model. Thus it minimize the overhead compared to other data augmentation learning techniques.

Find a file

Harle, Antoine (Contracteur) 4f5a309bcc Ignore sample dir		2019-11-11 17:03:31 -05:00
FAR-HO	Initial Commit	2019-11-08 11:28:06 -05:00
Gradient-Descent-The-Ultimate-Optimizer	Initial Commit	2019-11-08 11:28:06 -05:00
higher	Ajout des TF multiples sequentielles	2019-11-11 17:01:15 -05:00
.gitignore	Ignore sample dir	2019-11-11 17:03:31 -05:00