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Uncertainty Quantification

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TitleStatusHype
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift—0
Hyperparameter Ensembles for Robustness and Uncertainty QuantificationCode0
Expert-Supervised Reinforcement Learning for Offline Policy Learning and EvaluationCode1
Output-Weighted Optimal Sampling for Bayesian Experimental Design and Uncertainty QuantificationCode1
Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence FunctionsCode0
Distribution-free binary classification: prediction sets, confidence intervals and calibrationCode1
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance AwarenessCode1
A Deterministic Approximation to Neural SDEs—0
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality—0
Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty QuantificationCode0
Uncertainty Quantification for Inferring Hawkes Networks—0
Uncertainty quantification using martingales for misspecified Gaussian processesCode0
Fast Deep Mixtures of Gaussian Process Experts—0
Conformal Inference of Counterfactuals and Individual Treatment EffectsCode1
Calibration of the von Wolffersdorff model using Genetic Algorithms—0
A generalized Bayes framework for probabilistic clustering—0
Physics Informed Deep Kernel Learning—0
Achieving Equalized Odds by Resampling Sensitive AttributesCode0
Bayesian Hidden Physics Models: Uncertainty Quantification for Discovery of Nonlinear Partial Differential Operators from Data—0
Sparse representation for damage identification of structural systems—0
Entropy-Regularized 2-Wasserstein Distance between Gaussian Measures—0
Uncertainty quantification in medical image segmentation with normalizing flowsCode1
A probabilistic generative model for semi-supervised training of coarse-grained surrogates and enforcing physical constraints through virtual observablesCode0
Variational-EM-Based Deep Learning for Noise-Blind Image Deblurring—0
Semi-supervised deep learning for high-dimensional uncertainty quantification—0
Uncertainty Evaluation Metric for Brain Tumour Segmentation—0
Physically interpretable machine learning algorithm on multidimensional non-linear fields—0
Detecting Adversarial Examples for Speech Recognition via Uncertainty QuantificationCode0
Causal Bayesian Optimization—0
Multi-view polarimetric scattering cloud tomography and retrieval of droplet size—0
Unsupervised Quality Estimation for Neural Machine TranslationCode1
A Bayesian - Deep Learning model for estimating Covid-19 evolution in SpainCode0
Uncertainty Quantification Using Neural Networks for Molecular Property PredictionCode1
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors—0
A Closed-Form Uncertainty Propagation in Non-Rigid Structure from MotionCode0
Large-scale Uncertainty Estimation and Its Application in Revenue Forecast of SMEs—0
Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models—0
Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network—0
Uncertainty Quantification for Hyperspectral Image Denoising Frameworks based on Low-rank Matrix ApproximationCode0
Deeply Uncertain: Comparing Methods of Uncertainty Quantification in Deep Learning AlgorithmsCode1
Multilevel and multifidelity uncertainty quantification for cardiovascular hemodynamics—0
Parameterizing uncertainty by deep invertible networks, an application to reservoir characterizationCode1
Hidden Markov Neural Networks—0
Model Uncertainty Quantification for Reliable Deep Vision Structural Health Monitoring—0
Stochastic spectral embedding—0
Industrial Forecasting with Exponentially Smoothed Recurrent Neural Networks—0
B-SCST: Bayesian Self-Critical Sequence Training for Image Captioning—0
Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approachCode1
From Fourier to Koopman: Spectral Methods for Long-term Time Series PredictionCode1
Variational Inference with Vine Copulas: An efficient Approach for Bayesian Computer Model CalibrationCode0
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