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MPhil in Machine Learning and Machine Intelligence


Posters from the Advanced Machine Learning module (MLMI 4)

Auto-Encoding Variational Bayes

Non-negative Matrix Factorisation

Semi-Supervised Learning with Deep Generative Models

Variational Inference in Deep Directed Latent Variable Models


Dissertations, August 2016, and posters presented at the Industry Day on 09 June 2016

 The  Generalised Gaussian Process Convolution Model                    Poster

Variable Length Word Encodings for Neural Translation Models         Poster

Model Uncertainty for Adversarial Examples Using Dropouts

BachBot: Automatic Composition in the Style of Bach Chorales          Poster

Integrated Predictive Entropy Search for Bayesian Optimization

One-shot Learning in Discriminative Neural Networks

ALTA Project - Spoken Language Assessment and Learning Improve Adaptation Performance of ASR to Non-Native Speakers     Poster

Probabilistic Programming in Julia: New Inference Algorithms            Poster

Active Learning for Historic Handwritten Text Recognition                  Poster


Extending Deep GPs: Novel Variational Inference Schemes and a GPU Implementation

Training Restricted Boltzmann Machines Using High-Temperature Expansions

Active Learning for High Dimensional Inputs using Bayesian Convolutional Neural Networks 

Automatically Grading Learners’ English using a Deep Gaussian Process

Optimising spoken dialogue systems using Gaussian process reinforcement learning for a large action set     Poster

Auto-Encoding with Stochastic Expectation Propagation in Latent Variable Models     Poster

Sparse Circular Gaussian Process Approximation Insights and Applications   Poster