APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Which of the following statements, when combined together, explain why we cannot train VAEs using Maximum likelihood Estimation?
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The decoder is parameterised by a neural network so it is highly non-linear
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The latent variable is continuous
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MLE requires evaluating the marginal distribution on data
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There are too many datapoints in the dataset
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Explanation:
Detailed explanation-1: -A generative model includes the distribution of the data itself, and tells you how likely a given example is. For example, models that predict the next word in a sequence are typically generative models (usually much simpler than GANs) because they can assign a probability to a sequence of words.
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