Uncertainty Quantification

Guaranteeing Robustness Against Real-World Perturbations In Time Series Classification Using Conformalized Randomized Smoothing UAI 2024 How to Fix a Broken Confidence Estimator: Evaluating Post-hoc Methods for Selective Classification with Deep Neural Networks UAI 2024 Identifying Homogeneous and Interpretable Groups for Conformal Prediction UAI 2024 Label-wise Aleatoric and Epistemic Uncertainty Quantification UAI 2024 Latent Representation Entropy Density for Distribution Shift Detection UAI 2024 Non-Exchangeable Conformal Risk Control ICLR 2024 Offline Bayesian Aleatoric and Epistemic Uncertainty Quantification and Posterior Value Optimisation in Finite-State MDPs UAI 2024 On Convergence of Federated Averaging Langevin Dynamics UAI 2024 On the Distance from Calibration in Sequential Prediction COLT 2024 Partial Identification with Proxy of Latent Confoundings via Sum-of-ratios Fractional Programming UAI 2024 Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance UAI 2024 Quantifying Local Model Validity using Active Learning UAI 2024 QuantProb: Generalizing Probabilities along with Predictions for a Pre-trained Classifier UAI 2024 Revisiting Kernel Attention with Correlated Gaussian Process Representation UAI 2024 SEL-BALD: Deep Bayesian Active Learning with Selective Labels NeurIPS 2024 Shedding Light on Large Generative Networks: Estimating Epistemic Uncertainty in Diffusion Models UAI 2024 Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning ICLR 2024 Uncertainty Estimation with Recursive Feature Machines UAI 2024 A Hierarchical Spatial Transformer for Massive Point Samples in Continuous Space NeurIPS 2023 Evidential Uncertainty and Diversity Guided Active Learning for Scene Graph Generation ICLR 2023 Learning Uncertainty for Unknown Domains with Zero-Target-Assumption ICLR 2023 NPCL: Neural Processes for Uncertainty-Aware Continual Learning NeurIPS 2023 On Compositional Uncertainty Quantification for Seq2seq Graph Parsing ICLR 2023 Preserving Pre-trained Features Helps Calibrate Fine-tuned Language Models ICLR 2023 Quantification of Uncertainty with Adversarial Models NeurIPS 2023