A new queryable binary dataset combining cross-build diversity, temporal history, and CVE labels with linked metadata for vulnerability research.
Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)
6 Pith papers cite this work, alongside 4,113 external citations. Polarity classification is still indexing.
6
Pith papers citing it
4,113
external citations · OpenAlex
years
2026 6verdicts
UNVERDICTED 6representative citing papers
smoothbp is an R package implementing fast Bayesian hierarchical piecewise regression with logistic smoothing, random effects, and spike-and-slab breakpoint selection via a custom Metropolis-within-Gibbs sampler in Rust.
A new Bayesian dynamic model integrates realized volatility proxies with price series via dynamic gamma processes and DLMs to enhance financial forecasting.
RG-inspired lattice models for piecewise GLMs provide explicit interpretable partitions and a replica-analysis-derived scaling law for regularization that allows increasing complexity without expected rise in generalization loss.
Develops a restricted MCAR model via reparameterization to measure and control informativeness in multivariate spatial modeling of health events across subgroups.
ProfileGLMM is an R package extending Bayesian profile regression with GLMMs to support hierarchical data, random effects, and cluster-covariate interactions for continuous or binary outcomes.
citing papers explorer
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ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage
A new queryable binary dataset combining cross-build diversity, temporal history, and CVE labels with linked metadata for vulnerability research.
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smoothbp: Fast Bayesian Hierarchical Piecewise Regression with Smoothed Transitions and Spike-and-Slab Model Selection
smoothbp is an R package implementing fast Bayesian hierarchical piecewise regression with logistic smoothing, random effects, and spike-and-slab breakpoint selection via a custom Metropolis-within-Gibbs sampler in Rust.
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Bayesian Dynamic Modeling of Realized Volatility in Financial Asset Price Forecasting
A new Bayesian dynamic model integrates realized volatility proxies with price series via dynamic gamma processes and DLMs to enhance financial forecasting.
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A renormalization-group inspired lattice-based framework for piecewise generalized linear models
RG-inspired lattice models for piecewise GLMs provide explicit interpretable partitions and a replica-analysis-derived scaling law for regularization that allows increasing complexity without expected rise in generalization loss.
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Restricted Multivariate Spatial Modeling
Develops a restricted MCAR model via reparameterization to measure and control informativeness in multivariate spatial modeling of health events across subgroups.
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ProfileGLMM: a R Package Extending Bayesian Profile Regression using Generalised Linear Mixed Models
ProfileGLMM is an R package extending Bayesian profile regression with GLMMs to support hierarchical data, random effects, and cluster-covariate interactions for continuous or binary outcomes.