User:Jadrian Miles/Thesis manifesto: probabilistic worldview

My dissertation involves solving three problems:

1. Automatically clustering tractography curves together so that the resulting clusters are neither too small (low reconstruction error, high model complexity) nor too big (high reconstruction error, low model complexity)
2. Automatically adjusting macrostructure elements to match input DWIs so that the elements' surfaces are neither too bumpy (low reconstruction error, high model complexity) nor too smooth (high reconstruction error, low model complexity)
3. Automatically adjusting microstructure properties within a given region in space to match input DWIs so that the spatial frequency of the microstructure parameters is neither too high (low reconstruction error, high model complexity) nor too low (high reconstruction error, low model complexity)

In each case, our goal is to balance the tradeoff between reconstruction error and model complexity. In order to do so in a principled fashion, we must define, for each case, what is meant by reconstruction error and model complexity.