uncertainty quantification

Knowing what You Know: valid and validated confidence sets in multiclass and multilabel prediction JMLR 2021 Laplace Redux - Effortless Bayesian Deep Learning NeurIPS 2021 Latent Derivative Bayesian Last Layer Networks AISTATS 2021 Learnable uncertainty under Laplace approximations UAI 2021 Learning and Planning Under Uncertainty for Green Security IJCAI 2021 Learning Prediction Intervals for Model Performance AAAI 2021 Learning Prediction Intervals for Regression: Generalization and Calibration AISTATS 2021 Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regression CVPR 2021 Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles CoRL 2021 LiBRe: A Practical Bayesian Approach to Adversarial Detection CVPR 2021 Linear-Time Probabilistic Solution of Boundary Value Problems NeurIPS 2021 Locally Valid and Discriminative Prediction Intervals for Deep Learning Models NeurIPS 2021 Meta-Learning Reliable Priors in the Function Space NeurIPS 2021 Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes AAAI 2021 Misclassification Risk and Uncertainty Quantification in Deep Classifiers WACV 2021 Multidimensional Uncertainty-Aware Evidential Neural Networks AAAI 2021 Multi-output Gaussian Processes for uncertainty-aware recommender systems UAI 2021 MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning ICML 2021 Nearest neighbor search under uncertainty UAI 2021 Neural Bootstrapper NeurIPS 2021 Non-asymptotic Confidence Intervals of Off-policy Evaluation: Primal and Dual Bounds ICLR 2021 Over-MAP: Structural Attention Mechanism and Automated Semantic Segmentation Ensembled for Uncertainty Prediction AAAI 2021 PAC Confidence Predictions for Deep Neural Network Classifiers ICLR 2021 PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees ICML 2021 Perception Beyond Sensors Under Uncertainty AAAI 2021