Figure 2: Variational Autoencoder Architecture for the UCI Digits Dataset The key point is that a VAE learns the distribution of its source data rather than memorizing the source data. A data ...

At 1 sample per pixel (spp), the Monte Carlo integration of indirect illumination results in very noisy images, and the problem can therefore be framed as reconstruction instead of denoising. Previous ...

The autoencoder has the same number of inputs and outputs (9) as the demo program, but for simplicity the illustrated autoencoder has architecture 9-2-9 (just 2 hidden nodes) instead of the 9-6-9 ...