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Uncertainty Quantification

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TitleStatusHype
Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests—0
Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation—0
Beyond the proton drip line: Bayesian analysis of proton-emitting nuclei—0
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems—0
Efficient Two-Stage Gaussian Process Regression Via Automatic Kernel Search and Subsampling—0
Advanced Stationary and Non-Stationary Kernel Designs for Domain-Aware Gaussian Processes—0
Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network—0
Adaptive Uncertainty Quantification for Scenario-based Control Using Meta-learning of Bayesian Neural Networks—0
Bivariate DeepKriging for Large-scale Spatial Interpolation of Wind Fields—0
Black-box Uncertainty Quantification Method for LLM-as-a-Judge—0
ELUQuant: Event-Level Uncertainty Quantification in Deep Inelastic Scattering—0
B-LSTM-MIONet: Bayesian LSTM-based Neural Operators for Learning the Response of Complex Dynamical Systems to Length-Variant Multiple Input Functions—0
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators—0
Advances in Surrogate Modeling for Biological Agent-Based Simulations: Trends, Challenges, and Future Prospects—0
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks—0
Empirical Validation of Conformal Prediction for Trustworthy Skin Lesions Classification—0
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data—0
Emulator-based global sensitivity analysis for flow-like landslide run-out models—0
Data-Informed Decomposition for Localized Uncertainty Quantification of Dynamical Systems—0
Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning—0
End-to-end Conditional Robust Optimization—0
End-to-End Probabilistic Framework for Learning with Hard Constraints—0
Enhanced multi-fidelity modelling for digital twin and uncertainty quantification—0
Bayesian Federated Learning for Continual Training—0
Harnessing On-Machine Metrology Data for Prints with a Surrogate Model for Laser Powder Directed Energy Deposition—0
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