techniques have been proposed for collaborative filtering. Some generalize traditional matrix factorization algorithms via a non-linear neural architecture, or leverage new model types like Variational Autoencoders. Deep learning has been applied to many scenarios (context-aware, sequence-aware, social tagging etc.).

However, deep learning effectiveness for collaborative recommendation has been questioned. A systematic analysis