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Uncertainty Quantification

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Showing 701–750 of 2366 papers

TitleStatusHype
Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification—0
Dimension-Free Average Treatment Effect Inference with Deep Neural Networks—0
Bayesian inference for data-efficient, explainable, and safe robotic motion planning: A review—0
Epistemic Uncertainty Quantification For Pre-trained Neural Network—0
Bayesian semi-supervised learning for uncertainty-calibrated prediction of molecular properties and active learning—0
An Overview of Large Language Models for Statisticians—0
Equivariant Representation Learning for Symmetry-Aware Inference with Guarantees—0
Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs—0
Bayesian Spike Train Inference via Non-Local Priors—0
Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods—0
Antithetic Noise in Diffusion Models—0
Disentangled Uncertainty and Out of Distribution Detection in Medical Generative Models—0
Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation—0
Distilling Calibration via Conformalized Credal Inference—0
Bayesian Imaging With Data-Driven Priors Encoded by Neural Networks: Theory, Methods, and Algorithms—0
Distributed estimation of the inverse Hessian by determinantal averaging—0
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model—0
Distributed Safe Learning and Planning for Multi-robot Systems—0
Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics—0
Distributional Actor-Critic Ensemble for Uncertainty-Aware Continuous Control—0
Distributionally Robust Statistical Verification with Imprecise Neural Networks—0
Distributionally robust uncertainty quantification via data-driven stochastic optimal control—0
Adaptive Uncertainty Quantification for Generative AI—0
Distribution-Driven Disjoint Prediction Intervals for Deep Learning—0
Epinet for Content Cold Start—0
Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents—0
Bayes without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating Projections—0
A comparative study of conformal prediction methods for valid uncertainty quantification in machine learning—0
Decision Theoretic Bootstrapping—0
Bayesian Hidden Physics Models: Uncertainty Quantification for Discovery of Nonlinear Partial Differential Operators from Data—0
Distribution-free uncertainty quantification for classification under label shift—0
Distribution free uncertainty quantification in neuroscience-inspired deep operators—0
Distribution-Free Uncertainty Quantification in Mechanical Ventilation Treatment: A Conformal Deep Q-Learning Framework—0
Diverse Randomized Value Functions: A Provably Pessimistic Approach for Offline Reinforcement Learning—0
Debiasing Mini-Batch Quadratics for Applications in Deep Learning—0
An Efficient and Uncertainty-aware Reinforcement Learning Framework for Quality Assurance in Extrusion Additive Manufacturing—0
Do Large Language Models (Really) Need Statistical Foundations?—0
Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks—0
Entropy-regularized Gradient Estimators for Approximate Bayesian Inference—0
Epistemic Deep Learning—0
DROMO: Distributionally Robust Offline Model-based Policy Optimization—0
Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks—0
Ensemble models outperform single model uncertainties and predictions for operator-learning of hypersonic flows—0
DSDE: Using Proportion Estimation to Improve Model Selection for Out-of-Distribution Detection—0
Bayesian Graph Contrastive Learning—0
Ensemble Neural Networks (ENN): A gradient-free stochastic method—0
Bayesian generative models can flag performance loss, bias, and out-of-distribution image content—0
DBCal: Density Based Calibration of classifier predictions for uncertainty quantification—0
Dual-Splitting Conformal Prediction for Multi-Step Time Series Forecasting—0
An Axiomatic Assessment of Entropy- and Variance-based Uncertainty Quantification in Regression—0
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