Unsupervised disentanglement is a long-standing challenge in representat...
Disentangling complex data to its latent factors of variation is a
funda...
Regularising the parameter matrices of neural networks is ubiquitous in
...
We introduce a new approach to understanding trained sequence neural mod...
Finding latent structures in data is drawing increasing attention in div...
Recurrent neural networks are widely used on time series data, yet such
...
We propose a method to simultaneously compute scalar basis functions wit...