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cs.CE2025
Nonparametric Stochastic Subspaces via the Bootstrap Method for Characterizing Model Error
Akash Yadav, Ruda Zhang
Reliable forward uncertainty quantification in engineering requires methods that account for aleatory and epistemic uncertainties. In many applications, epistemic effects arising f…
cs.LG2025
Bayesian Optimization under Uncertainty for Training a Scale Parameter in Stochastic Models
Akash Yadav, Ruda Zhang
Hyperparameter tuning is a challenging problem especially when the system itself involves uncertainty. Due to noisy function evaluations, optimization under uncertainty can be comp…
cs.CE2025★ 2 cited
Stochastic Subspace via Probabilistic Principal Component Analysis for Characterizing Model Error
Akash Yadav, Ruda Zhang
This paper proposes a probabilistic model of subspaces based on the probabilistic principal component analysis (PCA). Given a sample of vectors in the embedding space -- commonly k…