Bayesian Inference

Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving CoRL 2022 Path-Gradient Estimators for Continuous Normalizing Flows ICML 2022 PDQ-Net: Deep probabilistic dual quaternion network for absolute pose regression on $SE(3)$ UAI 2022 Phase transitions in when feedback is useful NeurIPS 2022 Physics Informed Deep Kernel Learning AISTATS 2022 Pick-and-Mix Information Operators for Probabilistic ODE Solvers AISTATS 2022 PInKS: Preconditioned Commonsense Inference with Minimal Supervision AACL 2022 Pixel Screening Based Intermediate Correction for Blind Deblurring CVPR 2022 Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction NeurIPS 2022 POEM: Out-of-Distribution Detection with Posterior Sampling ICML 2022 Possibilistic Logic Underlies Abstract Dialectical Frameworks IJCAI 2022 Posterior and Computational Uncertainty in Gaussian Processes NeurIPS 2022 Posterior Asymptotics for Boosted Hierarchical Dirichlet Process Mixtures JMLR 2022 Posterior Collapse of a Linear Latent Variable Model NeurIPS 2022 Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks NeurIPS 2022 Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm NeurIPS 2022 Preconditioning for Scalable Gaussian Process Hyperparameter Optimization ICML 2022 Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach AISTATS 2022 Predictive State Propensity Subclassification (PSPS): A causal inference algorithm for data-driven propensity score stratification CLeaR 2022 Predictive variational Bayesian inference as risk-seeking optimization AISTATS 2022 Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes AISTATS 2022 PrEF: Probabilistic Electricity Forecasting via Copula-Augmented State Space Model AAAI 2022 Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors NeurIPS 2022 PRISM: Probabilistic Real-Time Inference in Spatial World Models CoRL 2022 Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss NeurIPS 2022