When working with variational autoencoders, which objectives does the model try to achieve during the training process? Instruction: Choose all options that best answer the question. Minimize the sparsity of the neurons in the encoder Minimize the difference between the reconstructions and the original input Ensure that the learned distribution is a Gaussian distribution Maximize the number of dimensions used to represent the input image
When working with variational autoencoders, which objectives does the model try to achieve during the training process? Instruction: Choose all options that best answer the question. Minimize the sparsity of the neurons in the encoder Minimize the difference between the reconstructions and the original input Ensure that the learned distribution is a Gaussian distribution Maximize the number of dimensions used to represent the input image
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Transcribed Image Text:When working with variational autoencoders, which objectives does the model try to achieve during the training process?
Instruction: Choose all options that best answer the question.
Minimize the sparsity of the neurons in the encoder
Minimize the difference between the reconstructions and the original input
Ensure that the learned distribution is a Gaussian distribution
Maximize the number of dimensions used to represent the input image
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