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Uncertainty Quantification

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TitleStatusHype
Are vision language models robust to uncertain inputs?—0
A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers—0
Evaluating Aleatoric Uncertainty via Conditional Generative Models—0
Can Bayesian Neural Networks Make Confident Predictions?—0
Estimation and uncertainty quantification for piecewise smooth signal recovery—0
Calibration of the von Wolffersdorff model using Genetic Algorithms—0
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods—0
Estimating Uncertainty with Implicit Quantile Network—0
Calibration and Uncertainty Quantification of Bayesian Convolutional Neural Networks for Geophysical Applications—0
Estimating Uncertainty in PET Image Reconstruction via Deep Posterior Sampling—0
Estimating the reproductive number, total outbreak size, and reporting rates for Zika epidemics in South and Central America—0
Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding—0
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges—0
A Framework for Supervised and Unsupervised Segmentation and Classification of Materials Microstructure Images—0
Estimating Failure in Brittle Materials using Graph Theory—0
Estimating and Assessing Differential Equation Models with Time-Course Data—0
Essential Workers at Risk: An Agent-Based Model (SAFE-ABM) with Bayesian Uncertainty Quantification—0
Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models—0
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises—0
Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks—0
Calibrating Ensembles for Scalable Uncertainty Quantification in Deep Learning-based Medical Segmentation—0
Equivariant Representation Learning for Symmetry-Aware Inference with Guarantees—0
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation—0
A Framework for Strategic Discovery of Credible Neural Network Surrogate Models under Uncertainty—0
A computational spectral approach to interest rate models—0
A Bulirsch-Stoer algorithm using Gaussian processes—0
Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces—0
Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction—0
Epistemic Wrapping for Uncertainty Quantification—0
Are generative models fair? A study of racial bias in dermatological image generation—0
Epistemic Uncertainty Quantification For Pre-Trained Neural Networks—0
Epistemic Uncertainty Quantification For Pre-trained Neural Network—0
Epistemic Deep Learning—0
Calibrated Physics-Informed Uncertainty Quantification—0
A recursive Bayesian neural network for constitutive modeling of sands under monotonic loading—0
A framework for benchmarking uncertainty in deep regression—0
Epinet for Content Cold Start—0
Entropy-regularized Gradient Estimators for Approximate Bayesian Inference—0
Entropy-Regularized 2-Wasserstein Distance between Gaussian Measures—0
Stochasticity in Motion: An Information-Theoretic Approach to Trajectory Prediction—0
Entity Aware Modelling: A Survey—0
Ensemble Neural Networks (ENN): A gradient-free stochastic method—0
Calibrated and Enhanced NRLMSIS 2.0 Model with Uncertainty Quantification—0
A Fast, Reliable, and Secure Programming Language for LLM Agents with Code Actions—0
A Comprehensive Review of Digital Twin -- Part 2: Roles of Uncertainty Quantification and Optimization, a Battery Digital Twin, and Perspectives—0
Ensemble models outperform single model uncertainties and predictions for operator-learning of hypersonic flows—0
Ensemble learning and iterative training (ELIT) machine learning: applications towards uncertainty quantification and automated experiment in atom-resolved microscopy—0
Ensemble-based Uncertainty Quantification: Bayesian versus Credal Inference—0
Building Safe and Reliable AI systems for Safety Critical Tasks with Vision-Language Processing—0
Enhancing Trustworthiness in ML-Based Network Intrusion Detection with Uncertainty Quantification—0
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