no code implementations • 26 Nov 2020 • Luis A. Pérez Rey, Loek Tonnaer, Vlado Menkovski, Mike Holenderski, Jacobus W. Portegies
We propose a metric for the evaluation of the level of LSBD that a data representation achieves.
1 code implementation • NeurIPS 2021 • Loek Tonnaer, Luis A. Pérez Rey, Vlado Menkovski, Mike Holenderski, Jacobus W. Portegies
The definition of Linear Symmetry-Based Disentanglement (LSBD) formalizes the notion of linearly disentangled representations, but there is currently no metric to quantify LSBD.
no code implementations • 19 Mar 2020 • Luis A. Pérez Rey
A disentangled representation of a data set should be capable of recovering the underlying factors that generated it.
2 code implementations • 25 Jan 2019 • Luis A. Pérez Rey, Vlado Menkovski, Jacobus W. Portegies
A standard Variational Autoencoder, with a Euclidean latent space, is structurally incapable of capturing topological properties of certain datasets.