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Uncertainty Quantification

663 directly classified papers

Papers per year

Papers

Building Trust in Deep Learning System towards Automated Disease Detection AAAI 2019
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness NIPS 2019
Learning Confidence Sets using Support Vector Machines NIPS 2018
Predictive Uncertainty Estimation via Prior Networks NIPS 2018
Learning Structural Weight Uncertainty for Sequential Decision-Making AISTATS 2018
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty IJCAI 2018
Evidential Deep Learning to Quantify Classification Uncertainty NIPS 2018
Learning under Misspecified Objective Spaces CORL 2018
Accurate Uncertainties for Deep Learning Using Calibrated Regression ICML 2018
Reward Estimation for Variance Reduction in Deep Reinforcement Learning CORL 2018
To Trust Or Not To Trust A Classifier NIPS 2018
Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings ICML 2018
Discriminative Learning of Prediction Intervals AISTATS 2018
The Uncertainty Bellman Equation and Exploration ICML 2018
Implicit Probabilistic Integrators for ODEs NIPS 2018
Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning CORL 2017
Concrete Dropout NIPS 2017
Incorporating Uncertainty into Deep Learning for Spoken Language Assessment ACL 2017
Selective Classification for Deep Neural Networks NIPS 2017
Risk-sensitive Inverse Reinforcement Learning via Coherent Risk Models RSS 2017
Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests JMLR 2016
Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes NIPS 2015
Active Frame, Location, and Detector Selection for Automated and Manual Video Annotation CVPR 2014
Scaling Up Robust MDPs using Function Approximation ICML 2014
Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification ICML 2014