Uncertainty-Calibrated Collaborative Filtering via Heteroscedastic Bayesian Neural Networks
Although recommendation systems based on neural collaborative filtering (NCF) can achieve high rating accuracy, the point estimates they generate do not express prediction confidence. Existing variants that account for uncertainty, such as Monte Carlo dropout, deep ensemble models, and single-head Bayesian networks, ca...