Posters from the Advanced Machine Learning Module, June 2017
Auto-Encoding Variational Bayes
Sequential Neural Models with Stochastic Layers
Stacked Convolutional Auto-encoders for Hierarchical Feature Extraction
Importance Weighted Autoencoders
Semi-Supervised Learning with Deep Generative Models
Dissertations, August 2017, and Posters presented at the Industry Day on 19 June 2017
Tradeoffs in Neural Variational Inference * Poster
Memory Networks for Language Modelling
Pathologies of Deep Sparse Gaussian Process Regression
Waveform Level Synthesis
Wasserstein Generative Adversarial Network
Hierarchical Dialogue Management * Poster
Bayesian Deep Generative Models for Semi-Supervised and Active Learning * Poster
Improved Interpretability and Generalisation for Deep Learning
Constrained Bayesian Optimization for Automatic Chemical Design * Poster
Designing Neural Network Hardware Accelerators Using Deep Gaussian Processes
Neural Program Lattices: Learning through Weak Supervision * Poster
Natural Language to Neural Programs
Bayesian Neural Networks for K-Shot Learning * Poster
Bayes By Backprop Neural Networks for Dialogue Management
Improving Sample Efficiency for Gradient-Based Policy Optimisation * Poster
Sample Efficient Deep Reinforcement Learning for Dialogue Systems with Large Action Spaces