Abstract: According to one embodiment, a learning apparatus includes a first compressor, a generator, a second compressor, a discriminator and an updating unit. The first compressor generates a first latent variable from a sample using a first network. A generator generates a reconstruction sample from the first latent variable using a second network. The second compressor generates a second latent variable from the reconstruction sample using a third network. The calculator calculates a distance in a latent space between the first and second latent variables. The discriminator outputs a discrimination score using a fourth network. The updating unit trains the first to fourth networks based on the discrimination score and train the third network based on the distance.