2024
Subtractive Mixture Models via Squaring: Representation and Learning
Lorenzo Loconte, Aleksanteri Mikulus Sladek, Stefan Mengel, Martin Trapp, Arno Solin, Nicolas Gillis +1
ICLR 2024spotlight
Mixture models are traditionally represented and learned by adding several distributions as components. Allowing mixtures to subtract probability mass or density can drastically reduce the number of components needed to model complex distributions. However, learning such subtractive mixtures while e…