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Uncertainty Quantification

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Showing 1501–1550 of 2366 papers

TitleStatusHype
Graph Neural Networks in Modern AI-aided Drug Discovery—0
Fast Risk Assessment in Power Grids through Novel Gaussian Process and Active Learning—0
Graph Structure Learning with Interpretable Bayesian Neural Networks—0
Grassmannian diffusion maps based surrogate modeling via geometric harmonics—0
GUST: Quantifying Free-Form Geometric Uncertainty of Metamaterials Using Small Data—0
H-AddiVortes: Heteroscedastic (Bayesian) Additive Voronoi Tessellations—0
HappyMap: A Generalized Multi-calibration Method—0
Healing Gaussian Process Experts—0
Variation Due to Regularization Tractably Recovers Bayesian Deep Learning—0
Heteroscedastic Calibration of Uncertainty Estimators in Deep Learning—0
Hierarchical Gaussian Process Models for Regression Discontinuity/Kink under Sharp and Fuzzy Designs—0
Hierarchical shrinkage Gaussian processes: applications to computer code emulation and dynamical system recovery—0
Hierarchical Sparse Bayesian Multitask Model with Scalable Inference for Microbiome Analysis—0
Hierarchical Spatio-Temporal Uncertainty Quantification for Distributed Energy Adoption—0
Hierarchical Uncertainty Exploration via Feedforward Posterior Trees—0
High Confidence Level Inference is Almost Free using Parallel Stochastic Optimization—0
High-Dimensional Confidence Regions in Sparse MRI—0
Spatial best linear unbiased prediction: A computational mathematics approach for high dimensional massive datasets—0
High-Dimensional Uncertainty Quantification via Tensor Regression with Rank Determination and Adaptive Sampling—0
Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs—0
Homodyned K-distribution: parameter estimation and uncertainty quantification using Bayesian neural networks—0
HOMRS: High Order Metamorphic Relations Selector for Deep Neural Networks—0
How Certain are Uncertainty Estimates? Three Novel Earth Observation Datasets for Benchmarking Uncertainty Quantification in Machine Learning—0
How disentangled are your classification uncertainties?—0
How Good is the Bayes Posterior in Deep Neural Networks Really?—0
How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression—0
How much can change in a year? Revisiting Evaluation in Multi-Agent Reinforcement Learning—0
How To Make Your Cell Tracker Say "I dunno!"—0
Humble AI in the real-world: the case of algorithmic hiring—0
Humble your Overconfident Networks: Unlearning Overfitting via Sequential Monte Carlo Tempered Deep Ensembles—0
Hybrid uncertainty quantification for selective text classification in ambiguous tasks—0
Hyper Association Graph Matching with Uncertainty Quantification for Coronary Artery Semantic Labeling—0
Hyperdimensional Uncertainty Quantification for Multimodal Uncertainty Fusion in Autonomous Vehicles Perception—0
HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations—0
IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning—0
ICBM community cancer registry analysis: a focus on Non-Hodgkin Lymphoma cases in missileers—0
Identifying Bayesian Optimal Experiments for Uncertain Biochemical Pathway Models—0
Identifying Reliable Predictions in Detection Transformers—0
I Find Your Lack of Uncertainty in Computer Vision Disturbing—0
Image Super-Resolution with Guarantees via Conformalized Generative Models—0
Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep Learning—0
Implementing hosting capacity analysis in distribution networks: Practical considerations, advancements and future directions—0
(Implicit) Ensembles of Ensembles: Epistemic Uncertainty Collapse in Large Models—0
Credal Bayesian Deep Learning—0
Improved Active Learning via Dependent Leverage Score Sampling—0
Improved Calibration of Numerical Integration Error in Sigma-Point Filters—0
Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification—0
Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification—0
Improving Label Error Detection and Elimination with Uncertainty Quantification—0
Improving mathematical questioning in teacher training—0
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