Uncertainty Quantification

Beyond In-Domain Scenarios: Robust Density-Aware Calibration ICML 2023 Beyond Unimodal: Generalising Neural Processes for Multimodal Uncertainty Estimation NeurIPS 2023 BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming ICML 2023 Boosting Transductive Few-Shot Fine-Tuning With Margin-Based Uncertainty Weighting and Probability Regularization CVPR 2023 Bridging Precision and Confidence: A Train-Time Loss for Calibrating Object Detection CVPR 2023 Calibrating Multimodal Learning ICML 2023 Calibration by Distribution Matching: Trainable Kernel Calibration Metrics NeurIPS 2023 Causal Isotonic Calibration for Heterogeneous Treatment Effects ICML 2023 CoDrug: Conformal Drug Property Prediction with Density Estimation under Covariate Shift NeurIPS 2023 Confidence and Uncertainty Assessment for Distributional Random Forests JMLR 2023 Conformal Inference is (almost) Free for Neural Networks Trained with Early Stopping ICML 2023 Conformalization of Sparse Generalized Linear Models ICML 2023 Conformalized Unconditional Quantile Regression AISTATS 2023 Conformal Meta-learners for Predictive Inference of Individual Treatment Effects NeurIPS 2023 Conformal Off-Policy Prediction AISTATS 2023 Conformal PID Control for Time Series Prediction NeurIPS 2023 Conformal Prediction for Federated Uncertainty Quantification Under Label Shift ICML 2023 Conformal Prediction Sets for Graph Neural Networks ICML 2023 Conformal Prediction Sets for Ordinal Classification NeurIPS 2023 Conformal Prediction with Missing Values ICML 2023 DARL: Distance-Aware Uncertainty Estimation for Offline Reinforcement Learning AAAI 2023 Decoupling MaxLogit for Out-of-Distribution Detection CVPR 2023 Deep Deterministic Uncertainty: A New Simple Baseline CVPR 2023 Did You Mean...? Confidence-based Trade-offs in Semantic Parsing EMNLP 2023 Distance-to-Set Priors and Constrained Bayesian Inference AISTATS 2023