Explores translations and homotheties, discussing their properties and practical applications in preserving geometric characteristics.
On Normalizing Flows explores data inference, generation, taxonomy, and practical applications in analyzing inverse problems.
Explores data augmentation as a key regularization method in deep learning, covering techniques like translations, rotations, and artistic style transfer.
Explores base changes, bijective linear applications, matrix transformations, and dimensions of kernel and image spaces.
