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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
Bayesian Graph Contrastive Learning—0
Bayesian Hidden Physics Models: Uncertainty Quantification for Discovery of Nonlinear Partial Differential Operators from Data—0
Bayesian Imaging With Data-Driven Priors Encoded by Neural Networks: Theory, Methods, and Algorithms—0
Bayesian inference for data-efficient, explainable, and safe robotic motion planning: A review—0
Bayesian Inference for Left-Truncated Log-Logistic Distributions for Time-to-event Data Analysis—0
Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction—0
Bayesian Kernelized Tensor Factorization as Surrogate for Bayesian Optimization—0
Bayesian learning of the optimal action-value function in a Markov decision process—0
Bayesian Learning to Optimize: Quantifying the Optimizer Uncertainty—0
Bayesian LSTM for indoor temperature modeling—0
Bayesian meta learning for trustworthy uncertainty quantification—0
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How—0
Bayesian multi--dipole localization and uncertainty quantification from simultaneous EEG and MEG recordings—0
Bayesian Neural Hawkes Process for Event Uncertainty Prediction—0
Bayesian Neural Network Inference via Implicit Models and the Posterior Predictive Distribution—0
Bayesian neural networks and dimensionality reduction—0
Bayesian neural networks for predicting uncertainty in full-field material response—0
Bayesian neural networks for weak solution of PDEs with uncertainty quantification—0
Bayesian non-parametric non-negative matrix factorization for pattern identification in environmental mixtures—0
Bayesian Numerical Methods for Nonlinear Partial Differential Equations—0
Bayesian optimized deep ensemble for uncertainty quantification of deep neural networks: a system safety case study on sodium fast reactor thermal stratification modeling—0
Bayesian Over-the-Air FedAvg via Channel Driven Stochastic Gradient Langevin Dynamics—0
Bayesian Physics-Informed Extreme Learning Machine for Forward and Inverse PDE Problems with Noisy Data—0
Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems—0
Bayesian Physics-informed Neural Networks for System Identification of Inverter-dominated Power Systems—0
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