Question 1

Figure from the original question paper Consider a neural network as shown in the figure with 2 input neurons, a hidden layer with 2 neurons (ReLU), and 1 output neuron (sigmoid).\ Weights are: Figure from the original question paper with no biases. Dropout probability is 0.5 on the hidden layer. Figure from the original question paper If the input vector\ is fed to this network, what is the expected output while testing? Network diagram: inputs x1, x2, hidden neurons h11, h12, output y, with weights w111 = 1, w112 = 0.5, w121 = -1, w122 = 1, w211 = 1, w212 = 1 Which of the following statements are true about a Convolutional (CONV) layer?