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Uncertainty Quantification

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Showing 1801–1850 of 2366 papers

TitleStatusHype
Locally Differentially Private Bayesian Inference—0
Graph Posterior Network: Bayesian Predictive Uncertainty for Node ClassificationCode1
Uncertainty quantification in a mechanical submodel driven by a Wasserstein-GAN—0
A deep learning driven pseudospectral PCE based FFT homogenization algorithm for complex microstructures—0
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification—0
Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte CarloCode0
Quantifying Epistemic Uncertainty in Deep Learning—0
Uncertainty Quantification For Low-Rank Matrix Completion With Heterogeneous and Sub-Exponential Noise—0
Probabilistic ODE Solutions in Millions of Dimensions—0
Merging Two Cultures: Deep and Statistical Learning—0
Conditional Variational Autoencoder for Learned Image Reconstruction—0
Statistical Finite Elements via Langevin DynamicsCode0
Centroid Approximation for Bootstrap: Improving Particle Quality at Inference—0
Extracting Dynamical Models from Data—0
Calibrate your listeners! Robust communication-based training for pragmatic speakersCode0
Is MC Dropout Bayesian?—0
Uncertainty Quantification in LV State Estimation Under High Shares of Flexible Resources—0
Uncertainty quantification in the Bradley-Terry-Luce model—0
An Uncertainty-aware Loss Function for Training Neural Networks with Calibrated Predictions—0
Uncertainty-aware GAN with Adaptive Loss for Robust MRI Image Enhancement—0
Robustness and Reliability When Training With Noisy Labels—0
Residual Overfit Method of Exploration—0
Δ-UQ: Accurate Uncertainty Quantification via Anchor Marginalization—0
Hierarchical Gaussian Process Models for Regression Discontinuity/Kink under Sharp and Fuzzy Designs—0
Lagrangian Inference for Ranking Problems—0
Out-of-Distribution Detection for Medical Applications: Guidelines for Practical EvaluationCode0
UNCERTAINTY QUANTIFICATION USING VARIATIONAL INFERENCE FOR BIOMEDICAL IMAGE SEGMENTATION—0
MURO: Deployment Constrained Reinforcement Learning with Model-based Uncertainty Regularized Batch Optimization—0
Distribution-Driven Disjoint Prediction Intervals for Deep Learning—0
Particle Based Stochastic Policy Optimization—0
Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?—0
Function-Space Variational Inference for Deep Bayesian Classification—0
Learning to Estimate Epistemic Uncertainty in Neural Networks—0
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How—0
Provably Calibrated Regression Under Distribution Drift—0
Non-stationary Gaussian process discriminant analysis with variable selection for high-dimensional functional dataCode0
Grassmannian diffusion maps based surrogate modeling via geometric harmonics—0
DynG2G: An Efficient Stochastic Graph Embedding Method for Temporal GraphsCode0
A neural multilevel method for high-dimensional parametric PDEs—0
Bayesian deep learning of affordances from RGB images—0
Uncertainty quantification in covid-19 spread: lockdown effects—0
Bayesian non-parametric non-negative matrix factorization for pattern identification in environmental mixtures—0
Accurate Remaining Useful Life Prediction with Uncertainty Quantification: a Deep Learning and Nonstationary Gaussian Process Approach—0
Remaining useful life prediction with uncertainty quantification: development of a highly accurate model for rotating machinery—0
A Physics inspired Functional Operator for Model Uncertainty Quantification in the RKHS—0
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty QuantificationCode2
Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression—0
A Data-Driven Uncertainty Quantification Method for Stochastic Economic Dispatch—0
Machine-Learned HASDM Model with Uncertainty Quantification—0
Uncertainty Quantification in Medical Image Segmentation with Multi-decoder U-Net—0
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