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Uncertainty Quantification

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Showing 1351–1400 of 2366 papers

TitleStatusHype
Uncertainty Aware Neural Network from Similarity and SensitivityCode1
Fairness Uncertainty Quantification: How certain are you that the model is fair?—0
Score-based Generative Modeling Through Backward Stochastic Differential Equations: Inversion and Generation—0
Kernel Methods are Competitive for Operator LearningCode1
Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantificationCode1
A Forward and Backward Compatible Framework for Few-shot Class-incremental Pill RecognitionCode0
Quantile Extreme Gradient Boosting for Uncertainty Quantification—0
Multidimensional Uncertainty Quantification for Deep Neural Networks—0
Goal-oriented Uncertainty Quantification for Inverse Problems via Variational Encoder-Decoder Networks—0
Uncertainty-Aware Null Space Networks for Data-Consistent Image ReconstructionCode0
Neural State-Space Models: Empirical Evaluation of Uncertainty QuantificationCode0
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model—0
Post-selection Inference for Conformal Prediction: Trading off Coverage for Precision—0
Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring—0
UnCRtainTS: Uncertainty Quantification for Cloud Removal in Optical Satellite Time SeriesCode1
Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning—0
Slideflow: Deep Learning for Digital Histopathology with Real-Time Whole-Slide VisualizationCode2
Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantificationCode0
Perspectives on AI Architectures and Co-design for Earth System Predictability—0
Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine LearningCode0
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry—0
Uncertainty Quantification for Recursive Estimation in Adaptive Safety-Critical Control—0
Bayesian neural networks via MCMC: a Python-based tutorialCode1
Multilevel CNNs for Parametric PDEs—0
Inferring networks from time series: a neural approachCode1
Towards Reliable Uncertainty Quantification via Deep Ensembles in Multi-output Regression Task—0
Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation—0
Laplacian Segmentation Networks Improve Epistemic Uncertainty QuantificationCode0
Object Pose Estimation with Statistical Guarantees: Conformal Keypoint Detection and Geometric Uncertainty PropagationCode1
Novel Class Discovery for 3D Point Cloud Semantic SegmentationCode1
Solving High-Dimensional Inverse Problems with Auxiliary Uncertainty via Operator Learning with Limited Data—0
Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical AnalysisCode0
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review—0
Adaptive Modeling of Uncertainties for Traffic Forecasting—0
Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field—0
Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review—0
Efficient Bayesian Physics Informed Neural Networks for Inverse Problems via Ensemble Kalman Inversion—0
Validation of uncertainty quantification metrics: a primer based on the consistency and adaptivity conceptsCode0
Uncertainty quantification in neural network classifiers -- a local linear approach—0
Lifelong Machine Learning Potentials—0
HappyMap: A Generalized Multi-calibration Method—0
Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural NetworksCode0
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification—0
Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis—0
Expectation consistency for calibration of neural networksCode0
Traffic State Estimation from Vehicle Trajectories with Anisotropic Gaussian ProcessesCode1
Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control—0
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing SymmetriesCode0
Multi-Head Multi-Loss Model CalibrationCode0
Toward Robust Uncertainty Estimation with Random Activation FunctionsCode0
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