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Uncertainty Quantification

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Showing 26–50 of 2366 papers

TitleStatusHype
Mitigating loss of variance in ensemble data assimilation: machine learning-based and distance-free localizations for better covariance estimation—0
Vine Copulas as Differentiable Computational GraphsCode3
Model-Agnostic, Temperature-Informed Sampling Enhances Cross-Year Crop Mapping with Deep Learning—0
Bridging Data-Driven and Physics-Based Models: A Consensus Multi-Model Kalman Filter for Robust Vehicle State Estimation—0
Beyond Sin-Squared Error: Linear-Time Entrywise Uncertainty Quantification for Streaming PCA—0
Statistical Machine Learning for Astronomy -- A TextbookCode2
Recursive KalmanNet: Deep Learning-Augmented Kalman Filtering for State Estimation with Consistent Uncertainty QuantificationCode1
A Fast, Reliable, and Secure Programming Language for LLM Agents with Code Actions—0
Improving Group Robustness on Spurious Correlation via Evidential AlignmentCode0
Structure and asymptotic preserving deep neural surrogates for uncertainty quantification in multiscale kinetic equations—0
Uncertainty-Masked Bernoulli Diffusion for Camouflaged Object Detection Refinement—0
Uncertainty-Aware Deep Learning for Automated Skin Cancer Classification: A Comprehensive Evaluation—0
Inv-Entropy: A Fully Probabilistic Framework for Uncertainty Quantification in Language ModelsCode1
Bayesian Probabilistic Matrix Factorization—0
Probabilistic Variational Contrastive Learning—0
Textual Bayes: Quantifying Uncertainty in LLM-Based Systems—0
LaDCast: A Latent Diffusion Model for Medium-Range Ensemble Weather ForecastingCode1
Flow Matching Meets PDEs: A Unified Framework for Physics-Constrained Generation—0
Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces—0
End-to-End Probabilistic Framework for Learning with Hard Constraints—0
Graph Neural Networks in Modern AI-aided Drug Discovery—0
Emulating compact binary population synthesis simulations with robust uncertainty quantification and model comparison: Bayesian normalizing flowsCode0
Antithetic Noise in Diffusion Models—0
Testing Hypotheses of Covariate Effects on Topics of DiscourseCode0
Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning—0
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