Dual Network Hawkes Process -- Analyzing Topic Transitions in Text-Based Social Cascades
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Updated
Sep 5, 2021 - C++
Dual Network Hawkes Process -- Analyzing Topic Transitions in Text-Based Social Cascades
Latent Dirichlet Allocation using Collapsed Gibbs sampling
Fast adaptive rejection sampler for R
Hidden Markov Hawkes Process - Model for Analyzing Topical Transitions in text based cascades in Social Networks.
Jointly model the accuracy of cognitive responses and item choices within a bayesian hierarchical framework as described by Culpepper and Balamuta (2015) <doi:10.1007/s11336-015-9484-7>. In addition, the package contains the datasets used within the analysis of the paper.
Gibbs sampler for the Distance Dependent Chinese Restaurant Process
Low-level primitives for collapsed Gibbs sampling in python and C++
Bayesian Factorization with Side Information in C++ with Python wrapper
A method for variant graph genotyping based on exact alignment of k-mers
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