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epistemic uncertainty

156 papers

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EU

Co-occurring keywords

uncertainty quantification (1365) aleatoric uncertainty (105) out-of-distribution detection (611) uncertainty estimation (639) bayesian neural network (201) neural network (6616) bayesian inference (1904) reinforcement learning (4122) active learning (1295) large language model (12755)

Papers

SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models EACL 2024
RACER: Epistemic Risk-Sensitive RL Enables Fast Driving with Fewer Crashes RSS 2024
Uncertainty Quantification for In-Context Learning of Large Language Models NAACL 2024
One Step Closer to Unbiased Aleatoric Uncertainty Estimation AAAI 2024
Full Bayesian Significance Testing for Neural Networks in Traffic Forecasting IJCAI 2024
Dynamic Knowledge Injection for AIXI Agents AAAI 2024
NeoRL: Efficient Exploration for Nonepisodic RL NIPS 2024
Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage? NIPS 2024
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs ICML 2023
Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions NIPS 2023
Probabilities Are Not Enough: Formal Controller Synthesis for Stochastic Dynamical Models with Epistemic Uncertainty AAAI 2023
Quantification of Uncertainty with Adversarial Models NIPS 2023
Optimistic Active Exploration of Dynamical Systems NIPS 2023
On the Calibration of Probabilistic Classifier Sets AISTATS 2023
USDNL: Uncertainty-Based Single Dropout in Noisy Label Learning AAAI 2023
Hybrid Uncertainty Quantification for Selective Text Classification in Ambiguous Tasks ACL 2023
The Unreasonable Effectiveness of Deep Evidential Regression AAAI 2023
Efficient Exploration via Epistemic-Risk-Seeking Policy Optimization ICML 2023
dugMatting: Decomposed-Uncertainty-Guided Matting ICML 2023
Collision Probability Matching Loss for Disentangling Epistemic Uncertainty from Aleatoric Uncertainty AISTATS 2023
On the Importance of Exploration for Generalization in Reinforcement Learning NIPS 2023
Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach AISTATS 2023
One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning NIPS 2023
Bayesian Optimization with Conformal Prediction Sets AISTATS 2023
Effective Bayesian Heteroscedastic Regression with Deep Neural Networks NIPS 2023