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Uncertainty Quantification

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Showing 2151–2200 of 2366 papers

TitleStatusHype
Interval Neural Networks as Instability Detectors for Image ReconstructionsCode0
Interval Neural Networks: Uncertainty ScoresCode0
On Calibration of Mixup Training for Deep Neural NetworksCode0
Nearest Neighbor Dirichlet MixturesCode0
Uncertainty Quantification for Demand Prediction in Contextual Dynamic Pricing—0
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data—0
Scalable Uncertainty for Computer Vision with Functional Variational Inference—0
Uncertainty Estimation Using a Single Deep Deterministic Neural NetworkCode1
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery—0
Uncertainty Quantification for Sparse Deep Learning—0
Composing Normalizing Flows for Inverse Problems—0
A Comparative Study of Machine Learning Models for Predicting the State of Reactive MixingCode0
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong LearningCode1
Learnable Bernoulli Dropout for Bayesian Deep Learning—0
Statistical aspects of nuclear mass models—0
On transfer learning of neural networks using bi-fidelity data for uncertainty propagation—0
How Good is the Bayes Posterior in Deep Neural Networks Really?—0
Uncertainty Quantification for Bayesian Optimization—0
PDE-NetGen 1.0: from symbolic PDE representations of physical processes to trainable neural network representationsCode1
Towards a Kernel based Uncertainty Decomposition Framework for Data and Models—0
Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions—0
Certified and fast computations with shallow covariance kernels—0
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty EstimationCode0
Finding Optimal Points for Expensive Functions Using Adaptive RBF-Based Surrogate Model Via Uncertainty Quantification—0
Building high accuracy emulators for scientific simulations with deep neural architecture search—0
Training Normalizing Flows with the Information Bottleneck for Competitive Generative ClassificationCode1
Tackling small eigen-gaps: Fine-grained eigenvector estimation and inference under heteroscedastic noise—0
A deep-learning based Bayesian approach to seismic imaging and uncertainty quantificationCode0
Considering discrepancy when calibrating a mechanistic electrophysiology modelCode0
Machine Learning for Clouds and Climate—0
On Semi-parametric Inference for BART—0
Simple and Scalable Epistemic Uncertainty Estimation Using a Single Deep Deterministic Neural Network—0
Healing Gaussian Process Experts—0
Optimal Uncertainty-guided Neural Network Training—0
A practical guide to pseudo-marginal methods for computational inference in systems biologyCode0
Detection of False Positive and False Negative Samples in Semantic SegmentationCode0
Solving Bayesian Inverse Problems via Variational Autoencoders—0
Regression with Uncertainty Quantification in Large Scale Complex Data—0
Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon—0
Epistemic Uncertainty Quantification in Deep Learning Classification by the Delta MethodCode0
AGEM: Solving Linear Inverse Problems via Deep Priors and SamplingCode0
Generalised Linear Models for Dependent Binary Outcomes with Applications to Household Stratified Pandemic Influenza DataCode0
Measuring Uncertainty through Bayesian Learning of Deep Neural Network StructureCode0
Replication-based emulation of the response distribution of stochastic simulators using generalized lambda distributions—0
Give me (un)certainty -- An exploration of parameters that affect segmentation uncertainty—0
Beyond Matérn: On A Class of Interpretable Confluent Hypergeometric Covariance Functions—0
Uncertainty Quantification in Ensembles of Honest Regression Trees using Generalized Fiducial Inference—0
AMPL: A Data-Driven Modeling Pipeline for Drug DiscoveryCode0
Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature ModelingCode0
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO—0
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