Probabilistic Modeling

On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes ICML 2021 On the Complexity of Sum-of-Products Problems over Semirings AAAI 2021 On the Convex Combination of Determinantal Point Processes ACML 2021 On the Learnability of Knowledge in Multi-Agent Logics IJCAI 2021 On the Out-of-distribution Generalization of Probabilistic Image Modelling NeurIPS 2021 Optimal Order Simple Regret for Gaussian Process Bandits NeurIPS 2021 Optimized auxiliary particle filters: adapting mixture proposals via convex optimization UAI 2021 Ordinal Historical Dependence in Graphical Event Models with Tree Representations AAAI 2021 Orientation Probabilistic Movement Primitives on Riemannian Manifolds CoRL 2021 Outlier-Robust Learning of Ising Models Under Dobrushin’s Condition COLT 2021 Out of a Hundred Trials, How Many Errors Does Your Speaker Verifier Make? Interspeech 2021 Out-of-Distribution Detection Using Union of 1-Dimensional Subspaces CVPR 2021 Parallel tempering on optimized paths ICML 2021 Partially Observed Exchangeable Modeling ICML 2021 Particle-Gibbs Sampling for Bayesian Feature Allocation Models JMLR 2021 Partition Function Estimation: A Quantitative Study IJCAI 2021 Pathwise Conditioning of Gaussian Processes JMLR 2021 PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming AISTATS 2021 Perturb-and-max-product: Sampling and learning in discrete energy-based models NeurIPS 2021 PixelPyramids: Exact Inference Models From Lossless Image Pyramids ICCV 2021 Point Processes for Competing Observations with Recurrent Networks (POPCORN): A Generative Model of EHR Data MLHC 2021 Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks ICML 2021 Post-hoc loss-calibration for Bayesian neural networks UAI 2021 Prediction-Centric Learning of Independent Cascade Dynamics from Partial Observations ICML 2021 Predictive Complexity Priors AISTATS 2021