Dropout

Dropout: A Simple Way to Prevent Neural Networks from Overfitting

Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, Ruslan Salakhutdinov · JMLR 2014

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Implement explicitly masked inverted dropout, distinguishing training, inference and both probability endpoints.

What you will implement

Complete one element-wise function; actual masked training and Monte Carlo moments are supplied, without a generalization claim or image benchmark reproduction.

• 103. Inverted Dropout: Explicit Masks and Expected Activations

  Implement explicitly masked inverted dropout, distinguishing training, inference and both probability endpoints.

  Complete one element-wise function; actual masked training and Monte Carlo moments are supplied, without a generalization claim or image benchmark reproduction.