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Uncertainty Quantification

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Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation—0
Batch simulations and uncertainty quantification in Gaussian process surrogate-based approximate Bayesian computation—0
BayesAdapter: Being Bayesian, Inexpensively and Robustly, via Bayesian Fine-tuning—0
Bayesian Analysis for Over-parameterized Linear Model via Effective Spectra—0
Bayesian Analysis of Interpretable Aging across Thousands of Lithium-ion Battery Cycles—0
Bayesian approach to model-based extrapolation of nuclear observables—0
Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants—0
Bayesian autoencoders with uncertainty quantification: Towards trustworthy anomaly detection—0
Bayesian Causal Forests for Longitudinal Data: Assessing the Impact of Part-Time Work on Growth in High School Mathematics Achievement—0
Bayesian data assimilation to support informed decision-making in individualised chemotherapy—0
Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification—0
Bayesian Deep Learning for Discrete Choice—0
Bayesian deep learning framework for uncertainty quantification in high dimensions—0
Bayesian Deep Learning Hyperparameter Search for Robust Function Mapping to Polynomials with Noise—0
Bayesian deep learning of affordances from RGB images—0
Bayesian Deep Learning via Stochastic Gradient MCMC with a Stochastic Approximation Adaptation—0
Bayesian Deep Neural Networks for Supervised Learning of Single-View Depth—0
Bayesian Dynamical System Identification With Unified Sparsity Priors And Model Uncertainty—0
Bayesian Entropy Neural Networks for Physics-Aware Prediction—0
Bayesian Evidential Learning for Few-Shot Classification—0
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification—0
Bayesian Vector AutoRegression with Factorised Granger-Causal Graphs—0
Bayesian Federated Learning for Continual Training—0
Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory—0
Bayesian generative models can flag performance loss, bias, and out-of-distribution image content—0
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