TRACE creates valid conformal prediction sets for complex generative models by scoring outputs via averaged denoising or velocity errors along stochastic transport paths instead of likelihoods.
Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools
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CONTRA generates sharp multi-dimensional conformal prediction regions by defining nonconformity scores as distances from the center in the latent space of a normalizing flow.
Bayesian deep learning method rankings are unstable at small sample sizes, dataset-dependent, and require uncertainty-aware evaluation using hierarchical models and minimum detectable difference curves.
citing papers explorer
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TRACE: Transport Alignment Conformal Prediction via Diffusion and Flow Matching Models
TRACE creates valid conformal prediction sets for complex generative models by scoring outputs via averaged denoising or velocity errors along stochastic transport paths instead of likelihoods.
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CONTRA: Conformal Prediction Region via Normalizing Flow Transformation
CONTRA generates sharp multi-dimensional conformal prediction regions by defining nonconformity scores as distances from the center in the latent space of a normalizing flow.
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Unstable Rankings in Bayesian Deep Learning Evaluation
Bayesian deep learning method rankings are unstable at small sample sizes, dataset-dependent, and require uncertainty-aware evaluation using hierarchical models and minimum detectable difference curves.