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Uncertainty Quantification

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Showing 1001–1050 of 2366 papers

TitleStatusHype
Learning particle swarming models from data with Gaussian processes—0
Analysis, forecasting and system identification of a floating offshore wind turbine using dynamic mode decomposition—0
Generative emulation of chaotic dynamics with coherent prior—0
Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks—0
Generative Latent Neural PDE Solver using Flow Matching—0
Generative Modelling with Tensor Train approximations of Hamilton--Jacobi--Bellman equations—0
Physics-constrained Bayesian inference of state functions in classical density-functional theory—0
Generative structured normalizing flow Gaussian processes applied to spectroscopic data—0
Generative vs. Discriminative modeling under the lens of uncertainty quantification—0
GeoFUSE: A High-Efficiency Surrogate Model for Seawater Intrusion Prediction and Uncertainty Reduction—0
Data-Driven Calibration of Prediction Sets in Large Vision-Language Models Based on Inductive Conformal Prediction—0
Give me (un)certainty -- An exploration of parameters that affect segmentation uncertainty—0
Global Framework for Emulation of Nuclear Calculations—0
Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learning—0
Bayesian deep learning of affordances from RGB images—0
Conformalized Link Prediction on Graph Neural Networks—0
Goal-oriented Uncertainty Quantification for Inverse Problems via Variational Encoder-Decoder Networks—0
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification—0
Inductive Conformal Prediction under Data Scarcity: Exploring the Impacts of Nonconformity Measures—0
Gradient-enhanced deep neural network approximations—0
Data-driven Bayesian Control of Port-Hamiltonian Systems—0
Grad-Shafranov equilibria via data-free physics informed neural networks—0
Bayesian Deep Learning Hyperparameter Search for Robust Function Mapping to Polynomials with Noise—0
Bayesian deep learning framework for uncertainty quantification in high dimensions—0
Daily Land Surface Temperature Reconstruction in Landsat Cross-Track Areas Using Deep Ensemble Learning With Uncertainty Quantification—0
Analog In-Memory Computing with Uncertainty Quantification for Efficient Edge-based Medical Imaging Segmentation—0
Adaptive Probabilistic Forecasting of Electricity (Net-)Load—0
Industrial Forecasting with Exponentially Smoothed Recurrent Neural Networks—0
Inference and Uncertainty Quantification for Noisy Matrix Completion—0
DADEE: Well-calibrated uncertainty quantification in neural networks for barriers-based robot safety—0
Bayesian Deep Learning for Discrete Choice—0
Cycles of Thought: Measuring LLM Confidence through Stable Explanations—0
Cycle Consistency-based Uncertainty Quantification of Neural Networks in Inverse Imaging Problems—0
Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification—0
An Algorithm for Sensor Data Uncertainty Quantification—0
Bayesian data assimilation to support informed decision-making in individualised chemotherapy—0
Current Methods for Drug Property Prediction in the Real World—0
Improving Uncertainty Quantification in Large Language Models via Semantic Embeddings—0
An AI-powered Bayesian generative modeling approach for causal inference in observational studies—0
CUPS: Improving Human Pose-Shape Estimators with Conformalized Deep Uncertainty—0
Adaptive modelling of anti-tau treatments for neurodegenerative disorders based on the Bayesian approach with physics-informed neural networks—0
Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games—0
An Uncertainty-aware Loss Function for Training Neural Networks with Calibrated Predictions—0
A Bayesian approach to quantifying uncertainties and improving generalizability in traffic prediction models—0
Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty—0
Crowd Counting with Decomposed Uncertainty—0
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks—0
An Active Learning Method for Diabetic Retinopathy Classification with Uncertainty Quantification—0
Improving Random Forests by Smoothing—0
Covariance-Free Sparse Bayesian Learning—0
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