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Uncertainty Quantification

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Showing 1851–1875 of 2366 papers

TitleStatusHype
Causal Estimation for Text Data with (Apparent) Overlap Violations—0
Causally-Aware Spatio-Temporal Multi-Graph Convolution Network for Accurate and Reliable Traffic Prediction—0
Center-fixing of tropical cyclones using uncertainty-aware deep learning applied to high-temporal-resolution geostationary satellite imagery—0
Centroid Approximation for Bootstrap: Improving Particle Quality at Inference—0
Certified and fast computations with shallow covariance kernels—0
Data-centric challenges with the application and adoption of artificial intelligence for drug discovery—0
Characterising User Transfer Amid Industrial Resource Variation: A Bayesian Nonparametric Approach—0
Clarifying Trust of Materials Property Predictions using Neural Networks with Distribution-Specific Uncertainty Quantification—0
Classification and Uncertainty Quantification of Corrupted Data using Semi-Supervised Autoencoders—0
Uncertainty Quantification for LLMs through Minimum Bayes Risk: Bridging Confidence and Consistency—0
CoCoAFusE: Beyond Mixtures of Experts via Model Fusion—0
Cocoon: Robust Multi-Modal Perception with Uncertainty-Aware Sensor Fusion—0
COIN: Uncertainty-Guarding Selective Question Answering for Foundation Models with Provable Risk Guarantees—0
Collaborative Deterministic-Probabilistic Forecasting for Real-World Spatiotemporal Systems—0
Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation—0
Combating Noise: Semi-supervised Learning by Region Uncertainty Quantification—0
Combined Data and Deep Learning Model Uncertainties: An Application to the Measurement of Solid Fuel Regression Rate—0
Combined State and Parameter Estimation in Level-Set Methods—0
Combining additivity and active subspaces for high-dimensional Gaussian process modeling—0
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review—0
Combining Confidence Elicitation and Sample-based Methods for Uncertainty Quantification in Misinformation Mitigation—0
Combining Statistical Depth and Fermat Distance for Uncertainty Quantification—0
Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring—0
Comparing the quality of neural network uncertainty estimates for classification problems—0
Comparison of Uncertainty Quantification with Deep Learning in Time Series Regression—0
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