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MPhil in Machine Learning and Machine Intelligence




Posters from the Advanced Machine Learning Module, June 2018

Dropout as A Variational Approximation to Bayesian Neural Networks

Sequential Neural Models with Stochastic Layers

Auto-Encoding Variational Bayes


Dissertations, August 2018, and Posters presented at the Industry Day on 18 June 2018

Fairness in Machine Learning with Causal Reasoning

Spectral Methods in Gaussian Process Approximations * Poster

Fashion Products Identification Using Bayesian Latent Variable Models

Well-Calibrated Bayesian Neural Networks Poster

Relation Classification Based on Deep Learning Approach * Poster

Augmenting Natural Language Generation with External Memory Modules in Spoken Dialogue Systems * Poster

Combining Sum Product Networks and Variational Autoencoders * Poster

Curiosity-Driven Reinforcement Learning for Dialogue Management * Poster   Paper at ICASSP 2018 - 2019


Generative Adversarial Networks for Speech Recognition Data Augmentation * Poster

Manifold Hamiltonian Dynamics for Variational Auto-Encoders * Poster

Neural Network Compression * Poster

Automatic Chemical Design with Molecular Graph Variational Autoencoders

3D Human Motion Synthesis with Recurrent Gaussian Processes * Poster

Deeper Understanding of Autophagy and pseudo-Autophagy through Latent-Space Analysis

Contextual Reasoning in Scene Understanding (Poster)

Defending a Speech Recogniser against Adversarial Examples (Poster)

Compressing Neural Networks

Overcoming Catastrophic Forgetting in Neural Machine Translation