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Uncertainty Quantification

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Showing 926–950 of 2366 papers

TitleStatusHype
On Fractional Moment Estimation from Polynomial Chaos Expansion—0
Statistical Mechanics of Dynamical System Identification—0
SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models—0
Extracting Usable Predictions from Quantized Networks through Uncertainty Quantification for OOD DetectionCode0
Validation of ML-UQ calibration statistics using simulated reference values: a sensitivity analysisCode0
Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized TasksCode2
A Priori Uncertainty Quantification of Reacting Turbulence Closure Models using Bayesian Neural NetworksCode0
Outlier-Detection for Reactive Machine Learned Potential Energy SurfacesCode0
Prediction of the SYM-H Index Using a Bayesian Deep Learning Method with Uncertainty Quantification—0
Uncertainty Quantification in Anomaly Detection with Cross-Conformal p-ValuesCode0
Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks—0
Generative Modelling with Tensor Train approximations of Hamilton--Jacobi--Bellman equations—0
Probabilistically Correct Language-based Multi-Robot Planning using Conformal Prediction—0
Physics-constrained polynomial chaos expansion for scientific machine learning and uncertainty quantification—0
Quantifying neural network uncertainty under volatility clustering—0
Uncertainty-Aware Evaluation for Vision-Language ModelsCode1
Word-Sequence Entropy: Towards Uncertainty Estimation in Free-Form Medical Question Answering Applications and Beyond—0
Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests—0
Accuracy-Preserving Calibration via Statistical Modeling on Probability SimplexCode0
Extending the Scope of Inference About Predictive Ability to Machine Learning Methods—0
Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods—0
Nonlinear Discrete-Time Observers with Physics-Informed Neural Networks—0
Uncertainty quantification in fine-tuned LLMs using LoRA ensemblesCode0
Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes—0
Training Bayesian Neural Networks with Sparse Subspace Variational InferenceCode0
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