The Gumbel-max trick is a method to draw a sample from a categorical distribution, given by
its unnormalized (log-) probabilities. Over the past years, the machine learning community …

We propose a generative model of paraphrase generation, that encourages syntactic
diversity by conditioning on an explicit syntactic sketch. We introduce Hierarchical …

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 …

Within the context of event modeling and understanding, we propose a new method for
neural sequence modeling that takes partially-observed sequences of discrete, external …

Successfully training Variational Autoencoders (VAEs) with a hierarchy of discrete latent
variables remains an area of active research. Vector-Quantised VAEs are a powerful …

Abstract Representation learning is crucial for processing sequential and discrete data, such
as text in natural language processing (NLP). From classical methods like topic modeling to …

This thesis marks a gratifying culmination of four years of my PhD research. Although I am
penning down this thesis alone, I feel that there are many individuals all along my PhD …

Deep learning provides us with ever-more-sophisticated neural networks that can be tuned
via gradient ascent to maximise some objective. Bayesian statistics provides us with a …