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Uncertainty Quantification

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Showing 1051–1100 of 2366 papers

TitleStatusHype
Do Bayesian imaging methods report trustworthy probabilities?—0
Deep Neural Operator Enabled Digital Twin Modeling for Additive Manufacturing—0
CVAE-SM: A Conditional Variational Autoencoder with Style Modulation for Efficient Uncertainty QuantificationCode0
Informativeness of Weighted Conformal PredictionCode0
ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse ProblemsCode0
A design specification for Critical Illness Digital Twins to cure sepsis: responding to the National Academies of Sciences, Engineering and Medicine Report: Foundational Research Gaps and Future Directions for Digital Twins—0
Uncertainty quantification in metric spaces—0
How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression—0
Uncertainty Quantification Metrics for Deep Regression—0
MERIT: Multi-view Evidential learning for Reliable and Interpretable liver fibrosis sTaging—0
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks—0
A comparative study of conformal prediction methods for valid uncertainty quantification in machine learning—0
Conformal Prediction for Natural Language Processing: A Survey—0
Accelerating Convergence in Bayesian Few-Shot ClassificationCode0
Random Pareto front surfacesCode0
Multivariate Bayesian Last Layer for Regression: Uncertainty Quantification and Disentanglement—0
Accounting for the Effects of Probabilistic Uncertainty During Fast Charging of Lithium-ion Batteries—0
Statistics and explainability: a fruitful alliance—0
Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design—0
Predicting Safety Misbehaviours in Autonomous Driving Systems using Uncertainty QuantificationCode0
Uncertainty quantification for iterative algorithms in linear models with application to early stopping—0
Implicit Generative Prior for Bayesian Neural NetworksCode0
Sensor Response-Time Reduction using Long-Short Term Memory Network Forecasting—0
Deep Evidential Learning for Radiotherapy Dose Prediction—0
Taming False Positives in Out-of-Distribution Detection with Human FeedbackCode0
FedSI: Federated Subnetwork Inference for Efficient Uncertainty Quantification—0
Automatic AI controller that can drive with confidence: steering vehicle with uncertainty knowledge—0
Uncertainty Quantification of Data-Driven Output Predictors in the Output Error Setting—0
Uncertainty Quantification on Graph Learning: A Survey—0
A Novel A.I Enhanced Reservoir Characterization with a Combined Mixture of Experts -- NVIDIA Modulus based Physics Informed Neural Operator Forward Model—0
Zadeh's Type-2 Fuzzy Logic Systems: Precision and High-Quality Prediction Intervals—0
Multiclass ROC—0
Enhancing Interval Type-2 Fuzzy Logic Systems: Learning for Precision and Prediction Intervals—0
QUTE: Quantifying Uncertainty in TinyML with Early-exit-assisted ensembles for model-monitoring—0
Generalizing Machine Learning Evaluation through the Integration of Shannon Entropy and Rough Set Theory—0
Adaptive Catalyst Discovery Using Multicriteria Bayesian Optimization with Representation LearningCode0
Analytical results for uncertainty propagation through trained machine learning regression models—0
Data-driven modeling and prediction of microglial cell dynamics in the ischemic penumbra—0
A variational neural Bayes framework for inference on intractable posterior distributionsCode0
Accelerating Ensemble Error Bar Prediction with Single Models Fits—0
Epistemic Uncertainty Quantification For Pre-trained Neural Network—0
Combining Statistical Depth and Fermat Distance for Uncertainty Quantification—0
Uncertainty Aware Tropical Cyclone Wind Speed Estimation from Satellite DataCode0
Leveraging viscous Hamilton-Jacobi PDEs for uncertainty quantification in scientific machine learningCode0
On the Independence Assumption in Neurosymbolic Learning—0
Uncertainty Quantification in Detecting Choroidal Metastases on MRI via Evolutionary Strategies—0
Inferring Change Points in High-Dimensional Regression via Approximate Message Passing—0
Diverse Randomized Value Functions: A Provably Pessimistic Approach for Offline Reinforcement Learning—0
Learning smooth functions in high dimensions: from sparse polynomials to deep neural networks—0
Towards detecting unanticipated bias in Large Language Models—0
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