Author

Joshua Chen

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Preprint Oct 2026

Copula Active Subspaces II: Error Decomposition, A Posteriori Estimation, and Sharpness of the Bounds

The Copula Active Subspaces (CAS) method of Part I estimates a non-Gaussian observation-noise density $\pi_{\boldsymbol{n}}$ from residual samples. Its KL divergence $\mathcal{D}_{\mathrm{KL}}(\pi_{\boldsymbol{n}}\,\|\,\widehat\pi_{\boldsymbol{n}})$ admits an exact decomposition into marginal, projection and reduced-de...

Joshua Chen, P. V. van Leeuwen · 1 citation

Preprint Sep 2026

Copula Active Subspaces I: A Score-Covariance Method for Reduced-Order Non-Gaussian Density Estimation

In Bayesian inference problems with non-Gaussian observation noise, the posterior is only as accurate as the noise density, and gradient-based samplers need that density and its gradient evaluable pointwise, whether from an explicit expression or from code, and without an inner solve. We propose Copula Active Subspaces...

Joshua Chen, P. V. van Leeuwen · 2 citations