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uncertainty quantification

1365 papers

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Also known as

UQ

Co-occurring keywords

uncertainty estimation (639) bayesian inference (1904) large language model (12755) conformal prediction (208) gaussian process (1198) variational inference (2069) out-of-distribution detection (611) epistemic uncertainty (156) neural network (6616) bayesian neural network (201)

Papers

Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent NIPS 2023
CoDrug: Conformal Drug Property Prediction with Density Estimation under Covariate Shift NIPS 2023
Probabilistic Exponential Integrators NIPS 2023
Distribution-Free Model-Agnostic Regression Calibration via Nonparametric Methods NIPS 2023
Unifying Predictions of Deterministic and Stochastic Physics in Mesh-reduced Space with Sequential Flow Generative Model NIPS 2023
Class-Conditional Conformal Prediction with Many Classes NIPS 2023
Implicit Manifold Gaussian Process Regression NIPS 2023
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts NIPS 2023
Single Image Depth Prediction Made Better: A Multivariate Gaussian Take CVPR 2023
LINe: Out-of-Distribution Detection by Leveraging Important Neurons CVPR 2023
UMat: Uncertainty-Aware Single Image High Resolution Material Capture CVPR 2023
Are Binary Annotations Sufficient? Video Moment Retrieval via Hierarchical Uncertainty-Based Active Learning CVPR 2023
Exploring and Exploiting Uncertainty for Incomplete Multi-View Classification CVPR 2023
Bayesian Spiked Laplacian Graphs JMLR 2023
Optimal Strategies for Reject Option Classifiers JMLR 2023
Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics JMLR 2023
Bayesian Calibration of Imperfect Computer Models using Physics-Informed Priors JMLR 2023
HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation JMLR 2023
Thin and deep Gaussian processes NIPS 2023
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks NIPS 2023
Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing NIPS 2023
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification NIPS 2023
Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics NIPS 2023
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods NIPS 2023
Differentiable and Stable Long-Range Tracking of Multiple Posterior Modes NIPS 2023