CInC Flow: Characterizable Invertible 3x3 Convolution

Understand

Normalizing flows are an essential alternative to GANs for generative modelling, which can be optimized directly on the maximum likelihood of the dataset.

• They also allow computation of the exact latent vector corresponding to an image since they are composed of invertible transformations.
• However, the requirement of invertibility of the transformation prevents standard and expressive neural network models such as CNNs from being directly used.
• Emergent convolutions were proposed to construct an invertible 3$\times$3 CNN layer using a pair of masked CNN layers, making them inefficient.