Probabilistic Modeling

Learning Temporal Evolution of Spatial Dependence with Generalized Spatiotemporal Gaussian Process Models JMLR 2022 Learning Tractable Probabilistic Models from Inconsistent Local Estimates NeurIPS 2022 Lifted Division for Lifted Hugin Belief Propagation AISTATS 2022 Limited Memory Influence Diagrams for Attribute Statistical Process Control with Variable Sample Sizes PGM 2022 Local Differential Privacy for Belief Functions AAAI 2022 Local-Global MCMC kernels: the best of both worlds NeurIPS 2022 Logical Credal Networks NeurIPS 2022 Loss as the Inconsistency of a Probabilistic Dependency Graph: Choose Your Model, Not Your Loss Function AISTATS 2022 Lossless Compression with Probabilistic Circuits ICLR 2022 Marginalising over Stationary Kernels with Bayesian Quadrature AISTATS 2022 MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC ICLR 2022 Measuring the robustness of Gaussian processes to kernel choice AISTATS 2022 Memory Augmented State Space Model for Time Series Forecasting IJCAI 2022 Mesoscopic modeling of hidden spiking neurons NeurIPS 2022 Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo NeurIPS 2022 Mixtures of Controlled Gaussian Processes for Dynamical Modeling of Deformable Objects L4DC 2022 Model inclusion lattice of coloured Gaussian graphical models for paired data PGM 2022 Modeling Label Correlations for Ultra-Fine Entity Typing with Neural Pairwise Conditional Random Field EMNLP 2022 Modelling Non-Smooth Signals with Complex Spectral Structure AISTATS 2022 MoReL: Multi-omics Relational Learning ICLR 2022 Motron: Multimodal Probabilistic Human Motion Forecasting CVPR 2022 MPC: Multi-View Probabilistic Clustering CVPR 2022 Multistate analysis with infinite mixtures of Markov chains UAI 2022 Multi-Task Processes ICLR 2022 Multivariate Quantile Function Forecaster AISTATS 2022