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Uncertainty Quantification

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Showing 2251–2300 of 2366 papers

TitleStatusHype
Minimal Achievable Sufficient Statistic LearningCode0
Efficient Deep Gaussian Process Models for Variable-Sized InputCode0
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High DimensionsCode0
Forecasting Wireless Demand with Extreme Values using Feature Embedding in Gaussian Processes—0
Seismic Bayesian evidential learning: Estimation and uncertainty quantification of sub-resolution reservoir properties—0
Bayesian Deep Learning via Stochastic Gradient MCMC with a Stochastic Approximation Adaptation—0
Functional Bayesian Neural Networks for Model Uncertainty Quantification—0
Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout—0
Perceptual Attention-based Predictive Control—0
Influence of image segmentation on one-dimensional fluid dynamics predictions in the mouse pulmonary arteries—0
NNVA: Neural Network Assisted Visual Analysis of Yeast Cell Polarization Simulation—0
Parametrization of stochastic inputs using generative adversarial networks with application in geology—0
Intent-Aware Probabilistic Trajectory Estimation for Collision Prediction with Uncertainty Quantification—0
Robust Deep Gaussian Processes—0
Data-driven Prognostics with Predictive Uncertainty Estimation using Ensemble of Deep Ordinal Regression Models—0
Data Augmentation for Bayesian Deep Learning—0
Latent Simplex Position Model: High Dimensional Multi-view Clustering with Uncertainty Quantification—0
Uncertainty quantification of molecular property prediction with Bayesian neural networks—0
Deep Fundamental Factor ModelsCode0
On the Computation and Applications of Large Dense Partial Correlation Networks—0
Crowd Counting with Decomposed Uncertainty—0
Deep learning observables in computational fluid dynamicsCode1
Combined State and Parameter Estimation in Level-Set Methods—0
Deep active subspaces - a scalable method for high-dimensional uncertainty propagationCode1
Binscatter RegressionsCode0
UQ-CHI: An Uncertainty Quantification-Based Contemporaneous Health Index for Degenerative Disease Monitoring—0
A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regimeCode0
A Simple Baseline for Bayesian Uncertainty in Deep LearningCode1
Predictive Uncertainty Quantification with Compound Density Networks—0
Bayesian semi-supervised learning for uncertainty-calibrated prediction of molecular properties and active learning—0
Uncertainty Quantification in Deep MRI Reconstruction—0
Bayesian active learning for optimization and uncertainty quantification in protein dockingCode0
Coupling the reduced-order model and the generative model for an importance sampling estimator—0
Modeling and inference of spatio-temporal protein dynamics across brain networksCode0
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled DataCode0
Deep Learning for Ranking Response Surfaces with Applications to Optimal Stopping Problems—0
Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models—0
Reliable deep-learning-based phase imaging with uncertainty quantificationCode0
Deep learning electromagnetic inversion with convolutional neural networks—0
Distribution-Free Uncertainty Quantification for Kernel Methods by Gradient Perturbations—0
Deep Uncertainty Quantification: A Machine Learning Approach for Weather ForecastingCode0
Extending classical surrogate modelling to high-dimensions through supervised dimensionality reduction: a data-driven approach—0
Surrogate-assisted Bayesian inversion for landscape and basin evolution modelsCode0
Evaluating Bayesian Deep Learning Methods for Semantic SegmentationCode0
Improved Calibration of Numerical Integration Error in Sigma-Point Filters—0
Surrogate-assisted parallel tempering for Bayesian neural learningCode0
Uncertainty quantification of molecular property prediction using Bayesian neural network models—0
Quantifying Uncertainties in Natural Language Processing Tasks—0
Evaluating Uncertainty Quantification in End-to-End Autonomous Driving Control—0
Langevin-gradient parallel tempering for Bayesian neural learningCode0
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