Probabilistic integral circuits (PICs) have been recently introduced as probabilistic models
enjoying the key ingredient behind expressive generative models: continuous latent …

Probabilistic circuits (PCs) is a unifying representation for probabilistic models that support
tractable inference. Numerous applications of PCs like controllable text generation depend …

Squared tensor networks (TNs) and their generalization as parameterized computational
graphs--squared circuits--have been recently used as expressive distribution estimators in …

We propose $\chi $-net, an intrinsically interpretable architecture combining the
compositional multilinear structure of tensor networks with the expressivity and efficiency of …

Probabilistic circuits (PCs) are a tractable representation of probability distributions allowing
for exact and efficient computation of likelihoods and marginals. Recent advancements have …