37 citations · 79 across the 15 of their papers we have counts for
4 papers · 1 filter
Regularising Deep Networks with Deep Generative Models
Matthew Willetts, Alexander Camuto, Stephen Roberts +1
We develop a new method for regularising neural networks. We learn a probability distribution over the activations of all layers of the model and then insert imputed values into th…
Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders
Matthew Willetts, Stephen Roberts, Chris Holmes
In clustering we normally output one cluster variable for each datapoint. However it is not necessarily the case that there is only one way to partition a given dataset into cluste…
Improving VAEs' Robustness to Adversarial Attack
Matthew Willetts, Alexander Camuto, Tom Rainforth +2
Variational autoencoders (VAEs) have recently been shown to be vulnerable to adversarial attacks, wherein they are fooled into reconstructing a chosen target image. However, how to…
Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels
Matthew Willetts, Stephen J Roberts, Christopher C Holmes
In semi-supervised learning for classification, it is assumed that every ground truth class of data is present in the small labelled dataset. Many real-world sparsely-labelled data…