Current Highlights

  • Some very simple Julia code for AutoDiff. Self explanatory I hope from the demos. See also note.
  • A note on AutoDiff, parameter tying in Deep Learning (Neural Nets) and Backprop Through Time.
  • Some preliminary ideas on solving ODEs using Gaussian Processes arxiv paper.

Recent research highlights

The auxiliary variable trick for deriving Kalman smoothers The derivation explains how to express the backward (beta) message in a form that is numerically stable.

MSC in Computational Statistics and Machine Learning

  • The MSC in Computational Statistics and Machine Learning is an exciting course that imparts key skills for analyzing our data rich world, including techniques for Information Retrieval and Machine Learning. We anticipate graduates from the programme to take key positions in research and leading organizations involved with large-scale information processing and analysis. The programme is taught by world-renowned researchers in Machine Learning from UCL Computer Science and the Gatsby Computational Neuroscience Unit.