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