Bayesian & Probabilistic

Social Media based Simulation Models for Understanding Disease Dynamics IJCAI 2018 Solving M-Modes in Loopy Graphs Using Tree Decompositions PGM 2018 Sound Abstraction and Decomposition of Probabilistic Programs ICML 2018 Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation CoRL 2018 Sparse Learning in Gaussian Chain Graphs for State Space Models PGM 2018 Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection ICML 2018 Stagewise Safe Bayesian Optimization with Gaussian Processes ICML 2018 State-by-state Minimax Adaptive Estimation for Nonparametric Hidden {M}arkov Models JMLR 2018 Stein Variational Gradient Descent as Moment Matching NeurIPS 2018 Stein Variational Message Passing for Continuous Graphical Models ICML 2018 Stochastic Nonparametric Event-Tensor Decomposition NeurIPS 2018 Stochastic Variance-Reduced Hamilton Monte Carlo Methods ICML 2018 Structured Factored Inference for Probabilistic Programming AISTATS 2018 Structured Inference for Recurrent Hidden Semi-markov Model IJCAI 2018 Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors ICML 2018 Structure Learning for Bayesian Networks over Labeled DAGs PGM 2018 Structure Learning Under Missing Data PGM 2018 Taming Performance Variability OSDI 2018 Temporal alignment and latent Gaussian process factor inference in population spike trains NeurIPS 2018 The Binary Space Partitioning-Tree Process AISTATS 2018 The Finite Model Theory of Bayesian Networks: Descriptive Complexity IJCAI 2018 The Mean-Field Approximation: Information Inequalities, Algorithms, and Complexity COLT 2018 The promises and pitfalls of Stochastic Gradient Langevin Dynamics NeurIPS 2018 Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning NeurIPS 2018 Tighter Variational Bounds are Not Necessarily Better ICML 2018