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01/19/2023
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs
U-Net architectures are ubiquitous in state-of-the-art deep learning, ho...
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06/09/2021
Multi-Facet Clustering Variational Autoencoders
Work in deep clustering focuses on finding a single partition of data. H...
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06/09/2021
I Don't Need 𝐮: Identifiable Non-Linear ICA Without Side Information
In this work we introduce a new approach for identifiable non-linear ICA...
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05/31/2021
Variational Autoencoders: A Harmonic Perspective
In this work we study Variational Autoencoders (VAEs) from the perspecti...
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02/15/2021
Certifiably Robust Variational Autoencoders
We introduce an approach for training Variational Autoencoders (VAEs) th...
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07/14/2020
Explicit Regularisation in Gaussian Noise Injections
We study the regularisation induced in neural networks by Gaussian noise...
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07/14/2020
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders
We make inroads into understanding the robustness of Variational Autoenc...
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07/14/2020
Relaxed-Responsibility Hierarchical Discrete VAEs
Successfully training Variational Autoencoders (VAEs) with a hierarchy o...
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02/18/2020
Learning Bijective Feature Maps for Linear ICA
Separating high-dimensional data like images into independent latent fac...
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01/30/2020
Non-Determinism in TensorFlow ResNets
We show that the stochasticity in training ResNets for image classificat...
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09/25/2019
Regularising Deep Networks with DGMs
Here we develop a new method for regularising neural networks where we l...
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09/25/2019
Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders
In clustering we normally output one cluster variable for each datapoint...
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06/01/2019
Disentangling Improves VAEs' Robustness to Adversarial Attacks
This paper is concerned with the robustness of VAEs to adversarial attac...
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01/24/2019
Semi-Unsupervised Learning with Deep Generative Models: Clustering and Classifying using Ultra-Sparse Labels
We introduce semi-unsupervised learning, an extreme case of semi-supervi...
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10/29/2018