lab 1: unsupervised pre-training, dropout and representation learning

@tachyeonz : For my first set of Pauli Space experiments, I thought I would start by attempting to answer elementary questions which might lead to more data efficient deep models and algorithms.

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Exploring alternative neural computational models

@tachyeonz : Despite different variations of neural networks architectures, the computational model of a neuron hasn’t changed since inception. Every neuron has \(n\) incoming inputs \(X = (x_{1}, x_{2}, …​, x_{n})\) with weights \(W = (w_{1}, w_{2}, …​, w_{n})\). A neuron then computes \(W.

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