Talk page

Title:
Variational Autoencoders: an introduction to new applications and a new regularization approach

Speaker:
Cedric Beaulac

Abstract:
In this presentation, we discuss the Variational AutoEncodeur (VAE): a latent variable model emerging from the machine learning community. To begin, we introduce the theoretical foundations of the model and its relationship with well-established statistical models. Then, we discuss how we used VAEs to solve two widely different problems. First, we tackled a classic statistical problem, survival analysis, and then a classic machine learning problems, image analysis and image generation. We conclude with a short discussion of our latest research project where we establish a new metric for the evaluation or regularization of latent variable models such a Gaussian Mixture Models and VAEs.​

Link:
https://mathtube.org/lecture/video/variational-autoencoders-introduction-new-applications-and-new-regularization-approach