Bayesian & Probabilistic

Encoding Probabilistic Graphical Models into Stochastic Boolean Satisfiability IJCAI 2022 End-to-End Probabilistic Label-Specific Feature Learning for Multi-Label Classification AAAI 2022 Entropy Estimation via Normalizing Flow AAAI 2022 Estimating Density Models with Truncation Boundaries using Score Matching JMLR 2022 Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network ICML 2022 Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing ICML 2022 Exact Community Recovery in Correlated Stochastic Block Models COLT 2022 Explaining Deep Tractable Probabilistic Models: The sum-product network case PGM 2022 Exploiting locality in high-dimensional Factorial hidden Markov models JMLR 2022 Exposing the Implicit Energy Networks behind Masked Language Models via Metropolis--Hastings ICLR 2022 FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns AAAI 2022 Fairness without the Sensitive Attribute via Causal Variational Autoencoder IJCAI 2022 Fast Bayesian Estimation of Point Process Intensity as Function of Covariates NeurIPS 2022 Fast Fourier Transform Reductions for Bayesian Network Inference AISTATS 2022 Fast Instrument Learning with Faster Rates NeurIPS 2022 Fat–Tailed Variational Inference with Anisotropic Tail Adaptive Flows ICML 2022 Feature Collapsing for Gaussian Process Variable Ranking AISTATS 2022 FedPop: A Bayesian Approach for Personalised Federated Learning NeurIPS 2022 Few-Shot Non-Parametric Learning with Deep Latent Variable Model NeurIPS 2022 Few-Shot Weakly-Supervised Object Detection via Directional Statistics WACV 2022 Fixed-Distance Hamiltonian Monte Carlo NeurIPS 2022 FlowHMM: Flow-based continuous hidden Markov models NeurIPS 2022 Flowification: Everything is a normalizing flow NeurIPS 2022 Forecasting Characteristic 3D Poses of Human Actions CVPR 2022 Foundation Posteriors for Approximate Probabilistic Inference NeurIPS 2022