C-SymmPI reformulates conditional coverage as miscoverage error over a user-specified function class to deliver near-conditional guarantees under group symmetries and distributional invariance.
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2026 2verdicts
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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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Conditional Predictive Inference for General Structured Data with Group Symmetries
C-SymmPI reformulates conditional coverage as miscoverage error over a user-specified function class to deliver near-conditional guarantees under group symmetries and distributional invariance.
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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.