Non-asymptotic decomposition of conditional miscoverage in conformal prediction into score-estimation error, finite-sample calibration error, and intrinsic conditional-mismatch error, with guidance for model selection and extensions to covariate shift and structured data.
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2026 10representative citing papers
Super-level-set regression directly optimizes conditional level-set boundaries via volume minimization to achieve minimum-volume prediction regions with conditional coverage.
SA-BCP adaptively blends temporal Bayesian predictions with spatial KDE evidence via threshold K, derives closed-form MSE-optimal K, and provides an online selection procedure with regret bounds, yielding sharper intervals at nominal coverage on volatility and weather data.
Temperature scaling of density-matrix eigenvalues from LLM semantic embeddings optimizes proper-score calibration and corrects systematic overconfidence so entropy equals risk.
Laplace approximation framework for quantile regression with mixed-effects and Gaussian processes using Fisher information and population curvature of expected loss instead of observed Hessian.
C-SymmPI reformulates conditional coverage as miscoverage error over a user-specified function class to deliver near-conditional guarantees under group symmetries and distributional invariance.
A meta-analytic framework estimates the resilience probability of a surrogate marker to the surrogate paradox in a new study by modeling deviations from functional relationships observed in completed trials.
Temporal difference calibration aligns uncertainty estimates in vision-language-action models with their value functions for better sequential performance.
A layered differentiable optimization approach combines conformal prediction for risk-aware ellipsoids with control barrier functions and quadratic programming for safe robot navigation under sensor uncertainty.
Tutorial on a statistical roadmap and R packages for selective borrowing in hybrid controlled trials, demonstrated on synthetic lung cancer data.
citing papers explorer
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A Unified Theory of Conditional Coverage in Conformal Prediction with Applications
Non-asymptotic decomposition of conditional miscoverage in conformal prediction into score-estimation error, finite-sample calibration error, and intrinsic conditional-mismatch error, with guidance for model selection and extensions to covariate shift and structured data.
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Super-Level-Set Regression: Conditional Quantiles via Volume Minimization
Super-level-set regression directly optimizes conditional level-set boundaries via volume minimization to achieve minimum-volume prediction regions with conditional coverage.
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Optimal Spatio-Temporal Decoupling for Bayesian Conformal Prediction
SA-BCP adaptively blends temporal Bayesian predictions with spatial KDE evidence via threshold K, derives closed-form MSE-optimal K, and provides an online selection procedure with regret bounds, yielding sharper intervals at nominal coverage on volatility and weather data.
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Eigenvalue Calibration for Semantic Embeddings of Large Language Models
Temperature scaling of density-matrix eigenvalues from LLM semantic embeddings optimizes proper-score calibration and corrects systematic overconfidence so entropy equals risk.
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Laplace Approximations for Mixed-Effects and Gaussian Process Quantile Regression
Laplace approximation framework for quantile regression with mixed-effects and Gaussian processes using Fisher information and population curvature of expected loss instead of observed Hessian.
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Conditional Predictive Inference for General Structured Data with Group Symmetries
C-SymmPI reformulates conditional coverage as miscoverage error over a user-specified function class to deliver near-conditional guarantees under group symmetries and distributional invariance.
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A Functional-Class Meta-Analytic Framework for Quantifying Surrogate Resilience
A meta-analytic framework estimates the resilience probability of a surrogate marker to the surrogate paradox in a new study by modeling deviations from functional relationships observed in completed trials.
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Temporal Difference Calibration in Sequential Tasks: Application to Vision-Language-Action Models
Temporal difference calibration aligns uncertainty estimates in vision-language-action models with their value functions for better sequential performance.
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Differentiable Optimization Layered Safety-Critical Control for Risk-Aware Navigation via Conformal Prediction
A layered differentiable optimization approach combines conformal prediction for risk-aware ellipsoids with control barrier functions and quadratic programming for safe robot navigation under sensor uncertainty.
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Robust Estimation and Inference with Selective Borrowing in Hybrid Controlled Trials: A Tutorial with SelectiveIntegrative and intFRT
Tutorial on a statistical roadmap and R packages for selective borrowing in hybrid controlled trials, demonstrated on synthetic lung cancer data.