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Model solves key challenge in combining mismatched geographic health data
Combining data across mismatched maps is a key challenge in global health and environmental research. A powerful modeling ...
Scientific Research Publishing5d
Generalized Bayesian Inference for Regression-Type Models with an Intractable Normalizing Constant ()
Regression models with intractable normalizing constants are valuable tools for analyzing complex data structures, yet ...
IEEE10d
Matrix-geometric solutions of M/G/1-type Markov chains: a unifying generalized state-space approach
Abstract: We present an algorithmic approach to find the stationary probability distribution of M/G/1-type Markov chains which arise frequently ... x/sub k/, is shown to be in the matrix-geometric ...
IEEE21d
Text-Rich Graph Neural Networks With Subjective-Objective Semantic Modeling
Specifically, we first introduce a new constrained Markov matrix with well-defined probabilistic diffusion dynamics to guide information propagation, where the neighbors are more appropriate and ...
GitHub23d
Markov Affinity-based Graph Imputation of Cells (MAGIC)
Markov Affinity-based Graph Imputation of Cells (MAGIC) is an algorithm for denoising high-dimensional data most commonly applied to single-cell RNA sequencing data. MAGIC learns the manifold data, ...