Machine Learning

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The original was posted on /r/machinelearning by /u/penguiny1205 on 2025-06-13 04:08:44+00:00.

During one of my experiments, I reduced the latent dimension of my autoencoder to 1, which yielded surprisingly good reconstructions of the input data. (See example below)

Reconstruction (blue) of input data (orange) with dim(Z) = 1

I was surprised by this. The first suspicion was that the autoencoder had entered one of its failure modes: ie, it was indexing data and "memorizing" it somehow. But a quick sweep across the latent space reveals that the singular latent parameter was capturing features in the data in a smooth and meaningful way. (See gif below) I thought this was a somewhat interesting observation!

Reconstructed data with latent parameter z taking values from -10 to 4. The real/encoded values of z have mean = -0.59 and std = 0.30.