deep learning

Comparison of various state-of-art reinforcement learning algorithms

A mathematical, in-depth tutorial about reinforcement learning presented to the lab members. This was to facilitate members to take up RL methods and apply them to their respective problem areas, as well as for myself to understand RL in an in-depth way.

This talk covers the first known application of reinforcement learning agents for landmark detection in CT Scans in medical imaging.

We propose a novel multi-metric voting scheme for evaluating machine translation systems.

Re-imagining the problem of word segmentation as a sequence prediction problem, predicting spaces between words in a sequence.

Convolutional neural networks based autoencoders for generating low-dimensional representations of brain MRI scans.