PLANE jointly estimates latent gene positions from a target network and proxy embeddings on a larger gene set, with provably optimal channel weighting and demonstrated gains in network recovery and imputation.
Journal of Business & Economic Statistics , volume=
3 Pith papers cite this work. Polarity classification is still indexing.
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stat.ME 3years
2026 3representative citing papers
Transfer learning from informative source networks improves target DCMM estimation accuracy by enlarging the eigenvalue gap of the connection probability matrix, with algorithms to avoid negative transfer.
A zero-inflated Poisson tensor model with shared low-rank, smooth, and clustered latent structure is proposed, with theory and empirical support.
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AI-Augmented Statistical Network Estimation with Proxy Gene Embeddings
PLANE jointly estimates latent gene positions from a target network and proxy embeddings on a larger gene set, with provably optimal channel weighting and demonstrated gains in network recovery and imputation.
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Transfer Learning for Degree-Corrected Mixed Membership Network Models
Transfer learning from informative source networks improves target DCMM estimation accuracy by enlarging the eigenvalue gap of the connection probability matrix, with algorithms to avoid negative transfer.
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A Probabilistic Model for Zero-Inflated Count Tensors with Structured Latent Representations
A zero-inflated Poisson tensor model with shared low-rank, smooth, and clustered latent structure is proposed, with theory and empirical support.