conftrace_

predictive uncertainty

79 papers

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PU

Co-occurring keywords

uncertainty quantification (1393) uncertainty estimation (648) out-of-distribution detection (617) variational inference (2069) neural network (6616) model calibration (232) bayesian deep learning (68) bayesian neural network (201) epistemic uncertainty (160) uncertainty calibration (58)

Papers

Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties AISTATS 2021
Detecting Compositionally Out-of-Distribution Examples in Semantic Parsing EMNLP 2021
Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models NIPS 2021
Laplace Redux - Effortless Bayesian Deep Learning NIPS 2021
Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes CORL 2021
Well-Calibrated Regression Uncertainty in Medical Imaging with Deep Learning MIDL 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness NIPS 2020
Predictive Uncertainty Estimation for Tractable Deep Probabilistic Models IJCAI 2020
Efficient Predictive Uncertainty Estimators for Deep Probabilistic Models AAAI 2020
Deep Gaussian Markov Random Fields ICML 2020
Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions ICML 2020
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties NIPS 2020
Non-Parametric Calibration for Classification AISTATS 2020
Transferable Calibration with Lower Bias and Variance in Domain Adaptation NIPS 2020
Estimating predictive uncertainty for rumour verification models ACL 2020
Neuronal Gaussian Process Regression NIPS 2020
Selective Dyna-Style Planning Under Limited Model Capacity ICML 2020
Deep Sigma Point Processes UAI 2020
Efficient Out-of-Distribution Detection in Digital Pathology Using Multi-Head Convolutional Neural Networks MIDL 2020
Learning for Single-Shot Confidence Calibration in Deep Neural Networks Through Stochastic Inferences CVPR 2019
Self-Supervised Mixture-of-Experts by Uncertainty Estimation AAAI 2019
Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference ICCV 2019
GOODE: A Gaussian Off-The-Shelf Ordinary Differential Equation Solver ICML 2019
Calibrated Model-Based Deep Reinforcement Learning ICML 2019
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks NIPS 2019