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Uncertainty Quantification

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Showing 1651–1700 of 2366 papers

TitleStatusHype
LLM Uncertainty Quantification through Directional Entailment Graph and Claim Level Response Augmentation—0
Local approximation of operators—0
Local Bayesian Dirichlet mixing of imperfect models—0
Locally Differentially Private Bayesian Inference—0
Logit Disagreement: OoD Detection with Bayesian Neural Networks—0
Looking at the posterior: accuracy and uncertainty of neural-network predictions—0
LoRA ensembles for large language model fine-tuning—0
Lyapunov-based uncertainty-aware safe reinforcement learning—0
Machine-Learned HASDM Model with Uncertainty Quantification—0
Machine learning-enabled velocity model building with uncertainty quantification—0
Machine Learning Enhances Algorithms for Quantifying Non-Equilibrium Dynamics in Correlation Spectroscopy Experiments to Reach Frame-Rate-Limited Time Resolution—0
Machine Learning for Clouds and Climate—0
Machine learning for graph-based representations of three-dimensional discrete fracture networks—0
Machine Learning for Predicting Chaotic Systems—0
Machine Learning for Robust Identification of Complex Nonlinear Dynamical Systems: Applications to Earth Systems Modeling—0
Uncertainty estimation of machine learning spatial precipitation predictions from satellite data—0
Machine learning models predict calculation outcomes with the transferability necessary for computational catalysis—0
Machine learning surrogates for efficient hydrologic modeling: Insights from stochastic simulations of managed aquifer recharge—0
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review—0
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models—0
Marginally-calibrated deep distributional regression—0
Marketing Mix Modeling in Lemonade—0
Masked Bayesian Neural Networks : Computation and Optimality—0
MaskVal: Simple but Effective Uncertainty Quantification for 6D Pose Estimation—0
Matrix Factorization for Inferring Associations and Missing Links—0
Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions—0
MD-split+: Practical Local Conformal Inference in High Dimensions—0
Medical Image Segmentation with Belief Function Theory and Deep Learning—0
Melanoma Detection with Uncertainty Quantification—0
Merging Two Cultures: Deep and Statistical Learning—0
MERIT: Multi-view Evidential learning for Reliable and Interpretable liver fibrosis sTaging—0
Meta-Learning Bayesian Neural Network Priors Based on PAC-Bayesian Theory—0
Meta-Learning Priors for Safe Bayesian Optimization—0
Meta-Learning Reliable Priors in the Function Space—0
Metrics for Benchmarking and Uncertainty Quantification: Quality, Applicability, and a Path to Best Practices for Machine Learning in Chemistry—0
Analysis of Diagnostics (Part I): Prevalence, Uncertainty Quantification, and Machine Learning—0
Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference—0
Mitigating Audiovisual Mismatch in Visual-Guide Audio Captioning—0
Mitigating loss of variance in ensemble data assimilation: machine learning-based and distance-free localizations for better covariance estimation—0
Mixtures of Laplace Approximations for Improved Post-Hoc Uncertainty in Deep Learning—0
Model-Agnostic, Temperature-Informed Sampling Enhances Cross-Year Crop Mapping with Deep Learning—0
Model-Agnostic Uncertainty Quantification for Fast NFC Tag Identification using RF Fingerprinting—0
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning—0
Model Architecture Adaption for Bayesian Neural Networks—0
Model-based Estimation of Difference-in-Differences with Staggered Treatments—0
Model-free generalized fiducial inference—0
Model-Free Local Recalibration of Neural Networks—0
Model-free system identification of surface ships in waves via Hankel dynamic mode decomposition with control—0
Modeling Uncertainty in 3D Gaussian Splatting through Continuous Semantic Splatting—0
Model orthogonalization and Bayesian forecast mixing via Principal Component Analysis—0
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