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Uncertainty Quantification

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Showing 1651–1700 of 2366 papers

TitleStatusHype
Fast Instrument Learning with Faster RatesCode0
The Unreasonable Effectiveness of Deep Evidential RegressionCode1
Uncertainty Quantification for Transport in Porous media using Parameterized Physics Informed neural Networks—0
Achieving Risk Control in Online Learning SettingsCode0
Exact Gaussian Processes for Massive Datasets via Non-Stationary Sparsity-Discovering Kernels—0
Finite Element Method-enhanced Neural Network for Forward and Inverse Problems—0
Bayesian Physics-Informed Extreme Learning Machine for Forward and Inverse PDE Problems with Noisy Data—0
A hybrid data driven-physics constrained Gaussian process regression framework with deep kernel for uncertainty quantification—0
Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems—0
Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep LearningCode0
Recurrent Encoder-Decoder Networks for Vessel Trajectory Prediction with Uncertainty Estimation—0
De-biasing "bias" measurementCode0
Extensible Machine Learning for Encrypted Network Traffic Application Labeling via Uncertainty Quantification—0
Large Scale Probabilistic Simulation of Renewables Production—0
A Unified Bayesian Framework for Pricing Catastrophe Bond Derivatives—0
Controlled Dropout for Uncertainty Estimation—0
Adversarial confound regression and uncertainty measurements to classify heterogeneous clinical MRI in Mass General BrighamCode0
A Deep Learning Approach to Dst Index Prediction—0
DeeptDCS: Deep Learning-Based Estimation of Currents Induced During Transcranial Direct Current Stimulation—0
A Survey on Uncertainty Toolkits for Deep Learning—0
Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replicability Study)Code1
ActPerFL: Active Personalized Federated Learning—0
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness—0
Deep Ensemble as a Gaussian Process Approximate Posterior—0
Tailored Uncertainty Estimation for Deep Learning Systems—0
A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement—0
Self-Aware Personalized Federated Learning—0
Conditional Injective Flows for Bayesian ImagingCode0
Disentangling Uncertainty in Machine Translation EvaluationCode1
Automated Learning of Interpretable Models with Quantified Uncertainty—0
A fully Bayesian sparse polynomial chaos expansion approach with joint priors on the coefficients and global selection of termsCode0
Deep learning-based surrogate model for 3-D patient-specific computational fluid dynamics—0
Bayesian Parameter Estimation for Dynamical Models in Systems BiologyCode0
RMFGP: Rotated Multi-fidelity Gaussian process with Dimension Reduction for High-dimensional Uncertainty Quantification—0
Uncertainty-Informed Deep Learning Models Enable High-Confidence Predictions for Digital HistopathologyCode2
MultiAuto-DeepONet: A Multi-resolution Autoencoder DeepONet for Nonlinear Dimension Reduction, Uncertainty Quantification and Operator Learning of Forward and Inverse Stochastic Problems—0
Deep-Ensemble-Based Uncertainty Quantification in Spatiotemporal Graph Neural Networks for Traffic Forecasting—0
Risk-Aware Control and Optimization for High-Renewable Power Grids—0
Probabilistic AutoRegressive Neural Networks for Accurate Long-range ForecastingCode0
DBCal: Density Based Calibration of classifier predictions for uncertainty quantification—0
Velocity continuation with Fourier neural operators for accelerated uncertainty quantificationCode0
On efficient algorithms for computing near-best polynomial approximations to high-dimensional, Hilbert-valued functions from limited samples—0
Bayesian Deep Learning with Multilevel Trace-class Neural Networks—0
SweiNet: Deep Learning Based Uncertainty Quantification for Ultrasound Shear Wave Elasticity ImagingCode0
Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty QuantificationCode1
Neural Message Passing for Objective-Based Uncertainty Quantification and Optimal Experimental DesignCode0
Prediction Sets Adaptive to Unknown Covariate ShiftCode0
Flexible Amortized Variational Inference in qBOLD MRICode0
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation—0
Bayesian Spatial Predictive Synthesis—0
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