Uncertainty in Deep Learning (PhD Thesis)

Uncertainty in Deep Learning(PhD Thesis) October 13th, 2016 Function draws from a dropout neural network. This new visualisation technique depicts the distribution over functions rather than the predictive distribution (see demo below). So I finally submitted my PhD thesis (given below). In it I organised the already published results on how to obtain uncertainty in deep learning, and collected lots of bits and pieces of new research I had lying around (which I hadn’t had the time to publish yet). The questions I got about the work over the past year were a great help in guiding my writing, with the greatest influence on my writing, I reckon, being the work of Professor Sir David MacKay (and his thesis specifically). Weirdly enough, I would consider David’s writing style to be…

Link to Full Article: Uncertainty in Deep Learning (PhD Thesis)

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