37 citations · 79 across the 15 of their papers we have counts for
4 papers · 1 filter
Multi-Facet Clustering Variational Autoencoders
Fabian Falck, Haoting Zhang, Matthew Willetts +3
Work in deep clustering focuses on finding a single partition of data. However, high-dimensional data, such as images, typically feature multiple interesting characteristics one co…
I Don't Need u: Identifiable Non-Linear ICA Without Side Information
Matthew Willetts, Brooks Paige
In this paper, we investigate the algorithmic stability of unsupervised representation learning with deep generative models, as a function of repeated re-training on the same input…
Variational Autoencoders: A Harmonic Perspective
Alexander Camuto, Matthew Willetts
In this work we study Variational Autoencoders (VAEs) from the perspective of harmonic analysis. By viewing a VAE's latent space as a Gaussian Space, a variety of measure space, we…
Certifiably Robust Variational Autoencoders
Ben Barrett, Alexander Camuto, Matthew Willetts +1
We introduce an approach for training Variational Autoencoders (VAEs) that are certifiably robust to adversarial attack. Specifically, we first derive actionable bounds on the mini…