NUTS-mul and NUTS-BPS show nearly identical qualitative ergodicity behavior depending on target tails, with both mixing in O(d^{1/4}) time for Gaussians but smaller constants for NUTS-BPS.
Equation of state calculations by fast computing machines.The journal of chemical physics, 21(6):1087–1092
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Ca extraction from post-spinel CaV2O4 is kinetically limited to at most half theoretical capacity at 298 K by high Ca migration barriers in the ordered γ phase and a persistent γ–δ two-phase region.
SecureForge audits LLM code for vulnerabilities, builds a synthetic prompt corpus via Markovian sampling, and optimizes system prompts to cut security issues by up to 48% while preserving unit test performance, with zero-shot transfer to real prompts.
A novel Bayesian copula-based model for joint multi-type spatio-temporal epidemic dynamics, with MCMC inference and validation on simulated data plus European meningococcal incidence records.
Structured Gaussian process classifier embeds graph-encoded biological pathways into the kernel for uncertainty-aware omics classification and reports gains over unstructured baselines on three microbiome datasets.
citing papers explorer
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A Theoretical Comparison of No-U-Turn Sampler Variants: Necessary and Sufficient Convergence Conditions and Mixing Time Analysis under Gaussian Targets
NUTS-mul and NUTS-BPS show nearly identical qualitative ergodicity behavior depending on target tails, with both mixing in O(d^{1/4}) time for Gaussians but smaller constants for NUTS-BPS.
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Phase stability and ionic transport in post-spinel CaV$_2$O$_4$ cathode
Ca extraction from post-spinel CaV2O4 is kinetically limited to at most half theoretical capacity at 298 K by high Ca migration barriers in the ordered γ phase and a persistent γ–δ two-phase region.
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SecureForge: Finding and Preventing Vulnerabilities in LLM-Generated Code via Prompt Optimization
SecureForge audits LLM code for vulnerabilities, builds a synthetic prompt corpus via Markovian sampling, and optimizes system prompts to cut security issues by up to 48% while preserving unit test performance, with zero-shot transfer to real prompts.
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Bayesian copula-based modelling for multi-type spatio-temporal epidemic data
A novel Bayesian copula-based model for joint multi-type spatio-temporal epidemic dynamics, with MCMC inference and validation on simulated data plus European meningococcal incidence records.
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Structured Gaussian Processes for Uncertainty-Aware Classification of High-Dimensional, Small-Sampled Omics Data
Structured Gaussian process classifier embeds graph-encoded biological pathways into the kernel for uncertainty-aware omics classification and reports gains over unstructured baselines on three microbiome datasets.