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uncertainty quantification

1365 papers

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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

Nearest neighbor search under uncertainty UAI 2021
Identifying regions of trusted predictions UAI 2021
Learnable uncertainty under Laplace approximations UAI 2021
Scaling Hamiltonian Monte Carlo inference for Bayesian neural networks with symmetric splitting UAI 2021
Distribution-free uncertainty quantification for classification under label shift UAI 2021
Trumpets: Injective flows for inference and inverse problems UAI 2021
Multi-output Gaussian Processes for uncertainty-aware recommender systems UAI 2021
Diagnostics for conditional density models and Bayesian inference algorithms UAI 2021
Proceedings of the thirty-seventh conference on Uncertainty in Artificial Intelligence — Preface UAI 2021
Subseasonal climate prediction in the western US using Bayesian spatial models UAI 2021
Bayesian Deep Graph Matching for Correspondence Identification in Collaborative Perception RSS 2021
Towards Propagation Uncertainty: Edge-enhanced Bayesian Graph Convolutional Networks for Rumor Detection IJCNLP 2021
Active Learning with Maximum Margin Sparse Gaussian Processes AISTATS 2021
Learning Prediction Intervals for Regression: Generalization and Calibration AISTATS 2021
Latent Derivative Bayesian Last Layer Networks AISTATS 2021
Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon AISTATS 2021
Calibrated Adaptive Probabilistic ODE Solvers AISTATS 2021
Improving Classifier Confidence using Lossy Label-Invariant Transformations AISTATS 2021
The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks JMLR 2021
From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction JMLR 2021
Knowing what You Know: valid and validated confidence sets in multiclass and multilabel prediction JMLR 2021
Asymptotic Normality, Concentration, and Coverage of Generalized Posteriors JMLR 2021
Misclassification Risk and Uncertainty Quantification in Deep Classifiers WACV 2021
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees ICML 2021
Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold ICML 2021