uncertainty quantification

Improving Training and Inference of Face Recognition Models via Random Temperature Scaling AAAI 2023 Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis AAAI 2023 Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach AISTATS 2023 Infinite-dimensional optimization and Bayesian nonparametric learning of stochastic differential equations JMLR 2023 Input uncertainty propagation through trained neural networks ICML 2023 Interactive Concept Bottleneck Models AAAI 2023 Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics JMLR 2023 Inverse-Reference Priors for Fisher Regularization of Bayesian Neural Networks AAAI 2023 JAWS-X: Addressing Efficiency Bottlenecks of Conformal Prediction Under Standard and Feedback Covariate Shift ICML 2023 Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares CVPR 2023 Learning Physical Models that Can Respect Conservation Laws ICML 2023 Learning Sample Difficulty from Pre-trained Models for Reliable Prediction NeurIPS 2023 Learn to Accumulate Evidence from All Training Samples: Theory and Practice ICML 2023 Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression NeurIPS 2023 LINe: Out-of-Distribution Detection by Leveraging Important Neurons CVPR 2023 Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation EACL 2023 Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference ICML 2023 MIND at SemEval-2023 Task 11: From Uncertain Predictions to Subjective Disagreement SemEval 2023 Mind the Biases: Quantifying Cognitive Biases in Language Model Prompting ACL 2023 MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability NeurIPS 2023 Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning NeurIPS 2023 Model-Based Uncertainty in Value Functions AISTATS 2023 Model-Bellman Inconsistency for Model-based Offline Reinforcement Learning ICML 2023 Modeling Multimodal Aleatoric Uncertainty in Segmentation with Mixture of Stochastic Experts ICLR 2023 Modeling the Distributional Uncertainty for Salient Object Detection Models CVPR 2023