bayesian inference

Knowledge-Aware Bayesian Deep Topic Model NeurIPS 2022 Knowledge Distillation via Constrained Variational Inference AAAI 2022 Knowledge Removal in Sampling-based Bayesian Inference ICLR 2022 Laplacian Autoencoders for Learning Stochastic Representations NeurIPS 2022 Learning Bayesian Sparse Networks With Full Experience Replay for Continual Learning CVPR 2022 Learning from Stochastically Revealed Preference NeurIPS 2022 Learning Not to Learn: Nature versus Nurture In Silico AAAI 2022 Limited Memory Influence Diagrams for Attribute Statistical Process Control with Variable Sample Sizes PGM 2022 Low-Precision Stochastic Gradient Langevin Dynamics ICML 2022 Marginal MAP estimation for inverse RL under occlusion with observer noise UAI 2022 Metalearning Linear Bandits by Prior Update AISTATS 2022 Meta Reinforcement Learning with Finite Training Tasks - a Density Estimation Approach NeurIPS 2022 Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo NeurIPS 2022 Multi-fidelity Monte Carlo: a pseudo-marginal approach NeurIPS 2022 Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data ACML 2022 Multi-Relational Graph Representation Learning with Bayesian Gaussian Process Network AAAI 2022 Multistate analysis with infinite mixtures of Markov chains UAI 2022 Natural Language to Code Translation with Execution EMNLP 2022 Non-Cheating Teaching Revisited: A New Probabilistic Machine Teaching Model IJCAI 2022 Nonlinear MCMC for Bayesian Machine Learning NeurIPS 2022 Nonparametric Involutive Markov Chain Monte Carlo ICML 2022 Nonparametric Relational Models with Superrectangulation AISTATS 2022 Numerical Approximations of Log Gaussian Cox Process (Student Abstract) AAAI 2022 Offline RL Policies Should Be Trained to be Adaptive ICML 2022 On Divergence Measures for Bayesian Pseudocoresets NeurIPS 2022