epistemic uncertainty

Collision Probability Matching Loss for Disentangling Epistemic Uncertainty from Aleatoric Uncertainty AISTATS 2023 Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization ICLR 2023 Deep Deterministic Uncertainty: A New Simple Baseline CVPR 2023 Deep Gaussian mixture ensembles UAI 2023 dugMatting: Decomposed-Uncertainty-Guided Matting ICML 2023 Effective Bayesian Heteroscedastic Regression with Deep Neural Networks NeurIPS 2023 Efficient Exploration via Epistemic-Risk-Seeking Policy Optimization ICML 2023 Estimating the Uncertainty in Emotion Attributes using Deep Evidential Regression ACL 2023 Exploration via Epistemic Value Estimation AAAI 2023 Gaussian Process Probes (GPP) for Uncertainty-Aware Probing NeurIPS 2023 Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors WACV 2023 Hallucinated adversarial control for conservative offline policy evaluation UAI 2023 Hybrid Uncertainty Quantification for Selective Text Classification in Ambiguous Tasks ACL 2023 Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach AISTATS 2023 Is the volume of a credal set a good measure for epistemic uncertainty? UAI 2023 Minimum Description Length Control ICLR 2023 Model-based Causal Bayesian Optimization ICLR 2023 Modeling the Distributional Uncertainty for Salient Object Detection Models CVPR 2023 Normalizing Flow Ensembles for Rich Aleatoric and Epistemic Uncertainty Modeling AAAI 2023 One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning NeurIPS 2023 On Second-Order Scoring Rules for Epistemic Uncertainty Quantification ICML 2023 On the Calibration of Probabilistic Classifier Sets AISTATS 2023 On the Importance of Exploration for Generalization in Reinforcement Learning NeurIPS 2023 Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs ICML 2023 Optimistic Active Exploration of Dynamical Systems NeurIPS 2023