A zero-inflated Poisson tensor model integrating low-rank CP structure, latent cluster embeddings, and smoothness is introduced for sparse single-cell Hi-C count tensors, with a Bayes-optimal zero distinction procedure, identifiability results, and consistency rates.
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Zero-inflated modeling with smoothing on counting tensors
A zero-inflated Poisson tensor model integrating low-rank CP structure, latent cluster embeddings, and smoothness is introduced for sparse single-cell Hi-C count tensors, with a Bayes-optimal zero distinction procedure, identifiability results, and consistency rates.