Bayesian Inference

Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression AAAI 2021 Precise characterization of the prior predictive distribution of deep ReLU networks NeurIPS 2021 Predictive Job Scheduling under Uncertain Constraints in Cloud Computing IJCAI 2021 Principled Exploration via Optimistic Bootstrapping and Backward Induction ICML 2021 Privately Publishable Per-instance Privacy NeurIPS 2021 Private Release of Text Embedding Vectors NAACL 2021 Probabilistic Attention for Interactive Segmentation NeurIPS 2021 Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning NAACL 2021 Probabilistic Forecasting: A Level-Set Approach NeurIPS 2021 Probabilistic Iterative Methods for Linear Systems JMLR 2021 Probabilistic Programs with Stochastic Conditioning ICML 2021 Probabilistic Robustness Quantification of Neural Networks AAAI 2021 Probabilistic selection of inducing points in sparse Gaussian processes UAI 2021 Probabilistic Tensor Decomposition of Neural Population Spiking Activity NeurIPS 2021 Probability Paths and the Structure of Predictions over Time NeurIPS 2021 Procedure Planning in Instructional Videos via Contextual Modeling and Model-Based Policy Learning ICCV 2021 Proceedings of the thirty-seventh conference on Uncertainty in Artificial Intelligence — Preface UAI 2021 Provable Guarantees on the Robustness of Decision Rules to Causal Interventions IJCAI 2021 Provably End-to-end Label-noise Learning without Anchor Points ICML 2021 pRSL: Interpretable multi-label stacking by learning probabilistic rules UAI 2021 Pseudo-Marginal Hamiltonian Monte Carlo JMLR 2021 q-Paths: Generalizing the geometric annealing path using power means UAI 2021 Quantifying Contextual Aspects of Inter-annotator Agreement in Intertextuality Research EMNLP 2021 Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding ICML 2021 Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models AISTATS 2021