2025
Unconditionally Calibrated Priors for Beta Mixture Density Networks
AISTATS 2025poster
Mixture Density Networks (MDNs) allow to model arbitrarily complex mappings between inputs and mixture densities, enabling flexible conditional density estimation, at the risk of severe overfitting. A Bayesian approach can alleviate this problem by specifying a prior over the parameters of the neura…