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Uncertainty Quantification

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TitleStatusHype
Variational-EM-Based Deep Learning for Noise-Blind Image Deblurring—0
Variational Shapley Network: A Probabilistic Approach to Self-Explaining Shapley values with Uncertainty Quantification—0
Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks—0
Verification of Neural Reachable Tubes via Scenario Optimization and Conformal Prediction—0
Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control—0
Weak in the NEES?: Auto-tuning Kalman Filters with Bayesian Optimization—0
Weakly Supervised Pixel-Level Annotation with Visual Interpretability—0
When Can We Reuse a Calibration Set for Multiple Conformal Predictions?—0
When Geoscience Meets Foundation Models: Towards General Geoscience Artificial Intelligence System—0
When Geoscience Meets Generative AI and Large Language Models: Foundations, Trends, and Future Challenges—0
When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer—0
Where Do We Go From Here? Guidelines For Offline Recommender Evaluation—0
Why Machine Learning Models Fail to Fully Capture Epistemic Uncertainty—0
With or Without Replacement? Improving Confidence in Fourier Imaging—0
Word-Sequence Entropy: Towards Uncertainty Estimation in Free-Form Medical Question Answering Applications and Beyond—0
WQLCP: Weighted Adaptive Conformal Prediction for Robust Uncertainty Quantification Under Distribution Shifts—0
Zadeh's Type-2 Fuzzy Logic Systems: Precision and High-Quality Prediction Intervals—0
Zebra: In-Context and Generative Pretraining for Solving Parametric PDEs—0
Zero-Shot Uncertainty Quantification using Diffusion Probabilistic Models—0
Fairness Uncertainty Quantification: How certain are you that the model is fair?—0
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks—0
Fair Uncertainty Quantification for Depression Prediction—0
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows—0
Fast Likelihood-Free Parameter Estimation for Lévy Processes—0
Fast Uncertainty Estimates in Deep Learning Interatomic Potentials—0
Fast Uncertainty Quantification for Deep Object Pose Estimation—0
Fast Uncertainty Quantification of Spent Nuclear Fuel with Neural Networks—0
Fast Value Tracking for Deep Reinforcement Learning—0
Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models—0
Federated Data Analytics: A Study on Linear Models—0
Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework—0
Federated Inference with Reliable Uncertainty Quantification over Wireless Channels via Conformal Prediction—0
FedPop: A Bayesian Approach for Personalised Federated Learning—0
FedSI: Federated Subnetwork Inference for Efficient Uncertainty Quantification—0
Feedforward neural networks as statistical models: Improving interpretability through uncertainty quantification—0
(f,Γ)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics—0
Finding Optimal Points for Expensive Functions Using Adaptive RBF-Based Surrogate Model Via Uncertainty Quantification—0
Fine-Grained Uncertainty Quantification via Collisions—0
Finite Element Method-enhanced Neural Network for Forward and Inverse Problems—0
Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling—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
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
Formal Verification and Control with Conformal Prediction—0
FREIDA: A Framework for developing quantitative agent based models based on qualitative expert knowledge—0
Frequentist Guarantees of Distributed (Non)-Bayesian Inference—0
From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence—0
From Classification Accuracy to Proper Scoring Rules: Elicitability of Probabilistic Top List Predictions—0
From FAIR to CURE: Guidelines for Computational Models of Biological Systems—0
From Physics to Foundation Models: A Review of AI-Driven Quantitative Remote Sensing Inversion—0
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