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Author

Run-Shi Tang

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Preprint Oct 2026

RECAP: Representation-Based Calibration with Amortized Pooling for Frequentist Simulation-Based Inference

Simulation-based inference enables uncertainty quantification in broad contexts when a simulation model is available but when a test statistic's sampling distribution is not tractable. But, frequentist calibration in this setting can be costly over high-dimensional parameter spaces. In this paper, we introduce RECAP (R...

Run-Shi Tang, Genevera I. Allen · 0 citations
Preprint Aug 2026

Bandable Cumulant Tensors: Optimal Estimation and Applications in Non-Gaussian Data Modeling

Higher-order cumulants capture the non-Gaussian dependence that covariance misses, but they are hard to use in high dimensions. An order-$d$ cumulant tensor has $p^d$ entries, and the plug-in sample cumulant is generally not even rate-optimal under the tensor spectral norm. For ordered data, both difficulties admit one...

Run-Shi Tang, An-Ru R. Zhang, Yuefeng Han et al. · 0 citations

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