Dissertations and Video Presentations from the class of 2019-2020
Woramanot Yomjinda: Dissertation: Lossless DNA Compression
Florian Langer: Dissertation: Precise Positioning of a Drone Using Spoken Language Commands
Can Xu: Dissertation: Matching Networks for Individual Organ Transplantation Allocation
Wen Wu Dissertation: Multimodal Emotion Recognition
Matt Ashman: Dissertation: Spatio-Temporal Variational Autoencoders
Ioannis Tsetis: Dissertation: Information-Theoretic Exploration with Successor Uncertainties
Alex Chan: Dissertation: Interpretable Policy Learning
Wenlong Chen: Dissertation: Improved Ergodic Inference via Kernelised Stein Discrepancy
Rui Xia: Dissertation: The Gaussian Process Latent Autoregressive Model
Conor Foy: Dissertation: Co-Activation Detection in Ten-Finger Typing on a Virtual Keyboard
Andrius Ovsianas: Dissertation: Interpretable Machine Learning
Tudor Paraschivescu: Dissertation: Multi-Output Gaussian Process Regression at Scale
Aliaksandra Shysheya: Dissertation: Neural Models for Non-Uniformly Sampled Data
Posters from the Advanced Machine Learning Module, June 2020
Doubly Stochastic Variational Inference for Deep Gaussian Processes
Practical Bayesian Optimization of Machine Learning Algorithms
Weight Uncertainty in Neural Networks