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Uncertainty Quantification

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Showing 1401–1450 of 2366 papers

TitleStatusHype
Bayesian Kernelized Tensor Factorization as Surrogate for Bayesian Optimization—0
A Survey on Uncertainty Quantification Methods for Deep Learning—0
Unsupervised Domain Adaptation for Low-dose CT Reconstruction via Bayesian Uncertainty AlignmentCode0
Forecasting Workload in Cloud Computing: Towards Uncertainty-Aware Predictions and Transfer LearningCode1
Model-Based Uncertainty in Value FunctionsCode1
Improving Adaptive Conformal Prediction Using Self-Supervised LearningCode1
Calibrated Regression Against An Adversary Without Regret—0
Learning Mixture Structure on Multi-Source Time Series for Probabilistic Forecasting—0
Data-driven reduced-order modelling for blood flow simulations with geometry-informed snapshotsCode0
Improved uncertainty quantification for neural networks with Bayesian last layerCode0
Learning Physical Models that Can Respect Conservation LawsCode1
Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles—0
Credal Bayesian Deep Learning—0
Bayesian Quantification with Black-Box EstimatorsCode0
Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions—0
Entity Aware Modelling: A Survey—0
Improved Online Conformal Prediction via Strongly Adaptive Online LearningCode1
B-BACN: Bayesian Boundary-Aware Convolutional Network for Crack Characterization—0
Probabilistic Circuits That Know What They Don't KnowCode1
Fixing Overconfidence in Dynamic Neural NetworksCode0
Event Temporal Relation Extraction with Bayesian Translational Model—0
On Fairness and Stability: Is Estimator Variance a Friend or a Foe?—0
A Benchmark on Uncertainty Quantification for Deep Learning PrognosticsCode1
Fortuna: A Library for Uncertainty Quantification in Deep LearningCode2
IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning—0
Clarifying Trust of Materials Property Predictions using Neural Networks with Distribution-Specific Uncertainty Quantification—0
Dropout Injection at Test Time for Post Hoc Uncertainty Quantification in Neural NetworksCode1
Generating Evidential BEV Maps in Continuous Driving SpaceCode1
Variational Inference on the Final-Layer Output of Neural NetworksCode0
Generalized Uncertainty of Deep Neural Networks: Taxonomy and Applications—0
Benchmarking Probabilistic Deep Learning Methods for License Plate RecognitionCode0
Physics Constrained Motion Prediction with Uncertainty Quantification—0
Randomized prior wavelet neural operator for uncertainty quantification—0
Hierarchical shrinkage Gaussian processes: applications to computer code emulation and dynamical system recovery—0
Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference—0
Convergence of uncertainty estimates in Ensemble and Bayesian sparse model discovery—0
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification—0
Incremental Value and Interpretability of Radiomics Features of Both Lung and Epicardial Adipose Tissue for Detecting the Severity of COVID-19 Infection—0
Combinatorial Inference on the Optimal Assortment in Multinomial Logit Models—0
From Classification Accuracy to Proper Scoring Rules: Elicitability of Probabilistic Top List Predictions—0
Conformal Prediction for Trustworthy Detection of Railway Signals—0
A Hybrid Deep Neural Operator/Finite Element Method for Ice-Sheet Modeling—0
Neural-Symbolic Inference for Robust Autoregressive Graph Parsing via Compositional Uncertainty Quantification—0
Adaptive Probabilistic Forecasting of Electricity (Net-)Load—0
Semiparametric inference using fractional posteriors—0
Physics-informed Information Field Theory for Modeling Physical Systems with Uncertainty QuantificationCode1
Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics—0
A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows—0
Uncertainty Quantification for Local Model Explanations Without Model AccessCode0
Constraining cosmological parameters from N-body simulations with Variational Bayesian Neural Networks—0
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