A new penalized geographically weighted compositional regression detects both contiguous and non-contiguous spatial clusters with shared effects when linking income distributions to COPD prevalence.
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4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
years
2026 4verdicts
UNVERDICTED 4representative citing papers
A Bayesian data-fusion model combines AI predictions and manual labels from camera traps to yield improved ecological inference and uncertainty quantification for white-tailed deer body condition.
A Bayesian model for multi-feature contact matrices that uses tensor structures and contingency table theory to satisfy structural constraints and impute missing contact features, validated on simulations and US/German survey data.
Donor-aware benchmarks show AUROCs up to 0.978 for IBD classification from scRNA-seq using CLR cell-type compositions and GatedStructuralCFN embeddings, with compartment stratification improving both performance and feature stability.
citing papers explorer
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Linking COPD Prevalence with Income Distribution: A Spatial Heterogeneous Compositional Regression via Geographically Weighted Penalized Approach
A new penalized geographically weighted compositional regression detects both contiguous and non-contiguous spatial clusters with shared effects when linking income distributions to COPD prevalence.
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Improving ecological inference and uncertainty quantification from camera trap data through the fusion of AI confidences and manual annotations
A Bayesian data-fusion model combines AI predictions and manual labels from camera traps to yield improved ecological inference and uncertainty quantification for white-tailed deer body condition.
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Bayesian Modeling and Prediction of Generalized Contact Matrices
A Bayesian model for multi-feature contact matrices that uses tensor structures and contingency table theory to satisfy structural constraints and impute missing contact features, validated on simulations and US/German survey data.
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Donor-Aware scRNA-seq Benchmarks for IBD Classification
Donor-aware benchmarks show AUROCs up to 0.978 for IBD classification from scRNA-seq using CLR cell-type compositions and GatedStructuralCFN embeddings, with compartment stratification improving both performance and feature stability.