Blog posts

2021

THE GEOMETRY OF DEEP GENERATIVE IMAGE MODELS AND ITS APPLICATIONS

Published:

This paper aims to make GAN inversion and interpretability possible. Through the lens of differential geometry, the authors propose that the metric tensor has various interpretability properties – by realising it as the Hessian matrix of the distance metric.

Score Based Generative Modeling Techniques

Published:

This report presents and summarizes the latest developments in Score based generative models – with a goal to enable better understanding of existing approaches, new sampling algorithms, exact likelihood computation and conditional generation abilties to the family of score based generative models.