uncertainty quantification

Identifiability Conditions for Domain Adaptation ICML 2022 iFS-RCNN: An Incremental Few-Shot Instance Segmenter CVPR 2022 Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging ICML 2022 Improving Bayesian Neural Networks by Adversarial Sampling AAAI 2022 Incomplete Argumentation Frameworks: Properties and Complexity AAAI 2022 Inference and Learning with Model Uncertainty in Probabilistic Logic Programs AAAI 2022 Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees NeurIPS 2022 Interpretable Self-Aware Neural Networks for Robust Trajectory Prediction CoRL 2022 Investigating Selective Prediction Approaches Across Several Tasks in IID, OOD, and Adversarial Settings ACL 2022 JAWS: Auditing Predictive Uncertainty Under Covariate Shift NeurIPS 2022 Latent Time Neural Ordinary Differential Equations AAAI 2022 Learning Domain Adaptive Object Detection with Probabilistic Teacher ICML 2022 Learning interacting dynamical systems with latent Gaussian process ODEs NeurIPS 2022 Learning Pareto-Efficient Decisions with Confidence AISTATS 2022 Learning Structured Gaussians To Approximate Deep Ensembles CVPR 2022 Learning to Map for Active Semantic Goal Navigation ICLR 2022 Low-Precision Stochastic Gradient Langevin Dynamics ICML 2022 Marginalising over Stationary Kernels with Bayesian Quadrature AISTATS 2022 Meta-Learning Priors for Safe Bayesian Optimization CoRL 2022 Mitigating the Effects of Non-Identifiability on Inference for Bayesian Neural Networks with Latent Variables JMLR 2022 Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief NeurIPS 2022 Modular Conformal Calibration ICML 2022 Multidimensional Belief Quantification for Label-Efficient Meta-Learning CVPR 2022 Multi-fidelity Monte Carlo: a pseudo-marginal approach NeurIPS 2022 Neural-Symbolic Inference for Robust Autoregressive Graph Parsing via Compositional Uncertainty Quantification EMNLP 2022