For an autoencoder anomaly detection system, model overfitting is characterized by a situation where all reconstructed inputs match the source inputs very closely, and therefore all reconstruction ...

Second, we use a second autoencoder to enhance the data representation of the reconstructed rating matrix, which can alleviate the loss of some key feature information during reconstruction.

This paper proposes a learning-based approach for reconstruction of global illumination with very low sampling budgets (as low as 1 spp) at interactive rates. At 1 sample per pixel (spp), the Monte ...