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Uncertainty Quantification

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Showing 1001–1050 of 2366 papers

TitleStatusHype
Characterising User Transfer Amid Industrial Resource Variation: A Bayesian Nonparametric Approach—0
Experiment Design with Gaussian Process Regression with Applications to Chance-Constrained Control—0
Generative emulation of chaotic dynamics with coherent prior—0
Data-centric challenges with the application and adoption of artificial intelligence for drug discovery—0
Generative Latent Neural PDE Solver using Flow Matching—0
Generative Modelling with Tensor Train approximations of Hamilton--Jacobi--Bellman equations—0
A generative foundation model for an all-in-one seismic processing framework—0
Generative structured normalizing flow Gaussian processes applied to spectroscopic data—0
A Critical Analysis of Internal Reliability for Uncertainty Quantification of Dense Image Matching in Multi-view Stereo—0
GeoFUSE: A High-Efficiency Surrogate Model for Seawater Intrusion Prediction and Uncertainty Reduction—0
Exact Gaussian Processes for Massive Datasets via Non-Stationary Sparsity-Discovering Kernels—0
Give me (un)certainty -- An exploration of parameters that affect segmentation uncertainty—0
EVIL: Evidential Inference Learning for Trustworthy Semi-supervised Medical Image Segmentation—0
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems—0
Certified and fast computations with shallow covariance kernels—0
Evidential time-to-event prediction with calibrated uncertainty quantification—0
Evidential Physics-Informed Neural Networks—0
A robustness measure for singular point and index estimation in discretized orientation and vector fields—0
A generalized Bayes framework for probabilistic clustering—0
Gradient-enhanced deep neural network approximations—0
Centroid Approximation for Bootstrap: Improving Particle Quality at Inference—0
Grad-Shafranov equilibria via data-free physics informed neural networks—0
Center-fixing of tropical cyclones using uncertainty-aware deep learning applied to high-temporal-resolution geostationary satellite imagery—0
A Risk-Aware Adaptive Robust MPC with Learned Uncertainty Quantification—0
Evidential Active Recognition: Intelligent and Prudent Open-World Embodied Perception—0
Event Temporal Relation Extraction with Bayesian Translational Model—0
Causally-Aware Spatio-Temporal Multi-Graph Convolution Network for Accurate and Reliable Traffic Prediction—0
A Comparative Study on Multi-task Uncertainty Quantification in Semantic Segmentation and Monocular Depth Estimation—0
Causal Estimation for Text Data with (Apparent) Overlap Violations—0
A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows—0
A General Framework for Uncertainty Quantification via Neural SDE-RNN—0
A Consistency-Based Loss for Deep Odometry Through Uncertainty Propagation—0
Evaluation of mathematical questioning strategies using data collected through weak supervision—0
Evaluation of Machine Learning Techniques for Forecast Uncertainty Quantification—0
Causal Bayesian Optimization—0
Evaluation of machine learning architectures on the quantification of epistemic and aleatoric uncertainties in complex dynamical systems—0
Evaluating Uncertainty Quantification in End-to-End Autonomous Driving Control—0
CATPlan: Loss-based Collision Prediction in End-to-End Autonomous Driving—0
Evaluating Uncertainty Quantification approaches for Neural PDEs in scientific applications—0
Evaluating Uncertainty Estimation Methods on 3D Semantic Segmentation of Point Clouds—0
Evaluating the Utility of Conformal Prediction Sets for AI-Advised Image Labeling—0
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods—0
Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis—0
Evaluating subgroup disparity using epistemic uncertainty in mammography—0
Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction—0
Evaluating probabilistic classifiers: Reliability diagrams and score decompositions revisited—0
Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?—0
Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery—0
Evaluating and Boosting Uncertainty Quantification in Classification—0
Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective—0
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