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Uncertainty Quantification

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Showing 1001–1050 of 2366 papers

TitleStatusHype
Relaxed Quantile Regression: Prediction Intervals for Asymmetric NoiseCode0
Exponentially Stable Projector-based Control of Lagrangian Systems with Gaussian Processes—0
Cycles of Thought: Measuring LLM Confidence through Stable Explanations—0
CSS: Contrastive Semantic Similarity for Uncertainty Quantification of LLMsCode0
The Deep Latent Space Particle Filter for Real-Time Data Assimilation with Uncertainty QuantificationCode0
Certifiably Byzantine-Robust Federated Conformal PredictionCode0
To Believe or Not to Believe Your LLM—0
Learning Cellular Network Connection Quality with Conformal—0
Integrating Physics of the Problem into Data-Driven Methods to Enhance Elastic Full-Waveform Inversion with Uncertainty QuantificationCode0
Label-wise Aleatoric and Epistemic Uncertainty QuantificationCode0
Offline Bayesian Aleatoric and Epistemic Uncertainty Quantification and Posterior Value Optimisation in Finite-State MDPsCode0
Robust Classification by Coupling Data Mollification with Label SmoothingCode0
Bayesian Joint Additive Factor Models for Multiview LearningCode0
A Structured Review of Literature on Uncertainty in Machine Learning & Deep Learning—0
Uncertainty Quantification for Bird's Eye View Semantic Segmentation: Methods and Benchmarks—0
Uncertainty Quantification for Deep Learning—0
Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning ApproachCode0
A Staged Approach using Machine Learning and Uncertainty Quantification to Predict the Risk of Hip Fracture—0
Bayesian Uncertainty Quantification for Anaerobic Digestion models—0
Conformal Depression PredictionCode0
Valid Conformal Prediction for Dynamic GNNsCode0
Verifiably Robust Conformal PredictionCode0
SEMF: Supervised Expectation-Maximization Framework for Predicting IntervalsCode0
BO4IO: A Bayesian optimization approach to inverse optimization with uncertainty quantificationCode0
Task-Driven Uncertainty Quantification in Inverse Problems via Conformal PredictionCode0
A Comparative Study on Multi-task Uncertainty Quantification in Semantic Segmentation and Monocular Depth Estimation—0
Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba—0
Kernel-based Optimally Weighted Conformal Prediction Intervals—0
Conformal Prediction for Ensembles: Improving Efficiency via Score-Based AggregationCode0
ProDAG: Projected Variational Inference for Directed Acyclic GraphsCode0
Uncertainty Quantification for Neurosymbolic Programs via Compositional Conformal Prediction—0
Score-based generative models are provably robust: an uncertainty quantification perspective—0
Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification—0
Hierarchical Uncertainty Exploration via Feedforward Posterior Trees—0
Reliable Trajectory Prediction and Uncertainty Quantification with Conditioned Diffusion Models—0
Stochastic Online Conformal Prediction with Semi-Bandit Feedback—0
Efficient Two-Stage Gaussian Process Regression Via Automatic Kernel Search and Subsampling—0
Regression Trees Know Calculus—0
A Deep Learning Approach to Multi-Fiber Parameter Estimation and Uncertainty Quantification in Diffusion MRI—0
Uncertainty quantification by block bootstrap for differentially private stochastic gradient descent—0
Gaussian Measures Conditioned on Nonlinear Observations: Consistency, MAP Estimators, and Simulation—0
Stochastic Inference of Plate Bending from Heterogeneous Data: Physics-informed Gaussian Processes via Kirchhoff-Love Theory—0
Conditional Shift-Robust Conformal Prediction for Graph Neural Network—0
Beyond Calibration: Assessing the Probabilistic Fit of Neural Regressors via Conditional Congruence—0
Efficient Line Search Method Based on Regression and Uncertainty Quantification—0
Model orthogonalization and Bayesian forecast mixing via Principal Component Analysis—0
Improving Label Error Detection and Elimination with Uncertainty Quantification—0
Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised LearningCode0
Multi-Source Conformal Inference Under Distribution ShiftCode0
The Pitfalls and Promise of Conformal Inference Under Adversarial AttacksCode0
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