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Uncertainty Quantification

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Showing 401–425 of 2366 papers

TitleStatusHype
B-SCST: Bayesian Self-Critical Sequence Training for Image Captioning—0
Bridging AI and Clinical Practice: Integrating Automated Sleep Scoring Algorithm with Uncertainty-Guided Physician Review—0
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data—0
Building Robust Machine Learning Models for Small Chemical Science Data: The Case of Shear Viscosity—0
Building Safe and Reliable AI systems for Safety Critical Tasks with Vision-Language Processing—0
Adversarial Attacks Against Uncertainty Quantification—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
Ablation Studies for Novel Treatment Effect Estimation Models—0
Advances in Surrogate Modeling for Biological Agent-Based Simulations: Trends, Challenges, and Future Prospects—0
B-LSTM-MIONet: Bayesian LSTM-based Neural Operators for Learning the Response of Complex Dynamical Systems to Length-Variant Multiple Input Functions—0
A recursive Bayesian neural network for constitutive modeling of sands under monotonic loading—0
Uncertainty-aware multi-fidelity surrogate modeling with noisy data—0
Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction—0
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation—0
Calibrating Ensembles for Scalable Uncertainty Quantification in Deep Learning-based Medical Segmentation—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
Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding—0
Calibration and Uncertainty Quantification of Bayesian Convolutional Neural Networks for Geophysical Applications—0
Calibration of the von Wolffersdorff model using Genetic Algorithms—0
Can Bayesian Neural Networks Make Confident Predictions?—0
Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective—0
Are vision language models robust to uncertain inputs?—0
Black-box Uncertainty Quantification Method for LLM-as-a-Judge—0
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