In a Variational Autoencoder (VAE), which component is responsible for encoding input data into a latent space representation?Question 27Answera. Encoderb.Latent Spacec.Decoderd.Sampler

What is a common architectural choice for the encoder network in Variational Autoencoders (VAEs) to capture complex dependencies in the input data?Question 2Answera.Convolutional layersb.Recurrent layersc.Recurrent layersd.Fully connected layers

Which type of Variational Autoencoder (VAE) variant focuses on generating structured and diverse  samples by conditioning the generation process on additional information?Question 1Answera.InfoVAEb.Beta-VAEc.Adversarial Autoencoder (AAE)d.Conditional VAE (CVAE

What are the encoder and decoder components of a transformer model?The encoder ingests an input sequence and produces a sequence of tokens. The decoder takes in the tokens from the encoder and produces an output sequence.The encoder ingests an input sequence and produces a single hidden state. The decoder takes in the hidden state from the encoder and produces an output sequence.The encoder ingests an input sequence and produces a sequence of hidden states. The decoder takes in the hidden states from the encoder and produces an output sequence.The encoder ingests an input sequence and produces a sequence of images. The decoder takes in the images from the encoder and produces an output sequence.

Variational AutoEncoder (use reconstruction error as the outlier score)

What is the main role of the decoder in a Transformer model?Question 14Answera.To generate output tokens based on the final encoder representation.b.To compute attention scores between input and output tokens.c.Learning positional encodings.d.To encode the input sequence.