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Uncertainty Quantification

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Showing 926–950 of 2366 papers

TitleStatusHype
(f,Γ)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics—0
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows—0
COIN: Uncertainty-Guarding Selective Question Answering for Foundation Models with Provable Risk Guarantees—0
Assessment of DeepONet for reliability analysis of stochastic nonlinear dynamical systems—0
Aggregation of Models, Choices, Beliefs, and Preferences—0
Fair Uncertainty Quantification for Depression Prediction—0
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks—0
Fairness Uncertainty Quantification: How certain are you that the model is fair?—0
Cocoon: Robust Multi-Modal Perception with Uncertainty-Aware Sensor Fusion—0
Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification—0
CoCoAFusE: Beyond Mixtures of Experts via Model Fusion—0
Uncertainty Quantification for LLMs through Minimum Bayes Risk: Bridging Confidence and Consistency—0
α-OCC: Uncertainty-Aware Camera-based 3D Semantic Occupancy Prediction—0
Forecasting Geopolitical Events with a Sparse Temporal Fusion Transformer and Gaussian Process Hybrid: A Case Study in Middle Eastern and U.S. Conflict Dynamics—0
A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation—0
Forecasting the future development in quality and value of professional football players for applications in team management—0
Forecasting Wireless Demand with Extreme Values using Feature Embedding in Gaussian Processes—0
Accelerating Ensemble Error Bar Prediction with Single Models Fits—0
Flow Matching Meets PDEs: A Unified Framework for Physics-Constrained Generation—0
Exploiting the Asymmetric Uncertainty Structure of Pre-trained VLMs on the Unit Hypersphere—0
Frequentist Guarantees of Distributed (Non)-Bayesian Inference—0
Extracting Dynamical Models from Data—0
Extensible Machine Learning for Encrypted Network Traffic Application Labeling via Uncertainty Quantification—0
Extending the Scope of Inference About Predictive Ability to Machine Learning Methods—0
Extending classical surrogate modelling to high-dimensions through supervised dimensionality reduction: a data-driven approach—0
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