AI, Machine Learning, Artificial Intelligence, Deep Learning, Data Science.
mean squared error (MSE) loss is the most commonly used loss function for reconstruction in autoencoders, which computes the average squared difference between the input and the output pixels. The goal is to minimize this loss function by adjusting the weights of the encoder and decoder networks.