Bayesian & Probabilistic

Robustness Guarantees for Bayesian Inference with Gaussian Processes AAAI 2019 Safe Exploration for Interactive Machine Learning NeurIPS 2019 Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers AISTATS 2019 Scalable Global Optimization via Local Bayesian Optimization NeurIPS 2019 Scalable inference of topic evolution via models for latent geometric structures NeurIPS 2019 Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data NeurIPS 2019 Self-Adversarially Learned Bayesian Sampling AAAI 2019 Semantic Alignment: Finding Semantically Consistent Ground-Truth for Facial Landmark Detection CVPR 2019 Semi-Parametric Sampling for Stochastic Bandits with Many Arms AAAI 2019 Sequential Neural Processes NeurIPS 2019 Smoothing Structured Decomposable Circuits NeurIPS 2019 Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs NeurIPS 2019 Spatial Mixture Models with Learnable Deep Priors for Perceptual Grouping AAAI 2019 SpHMC: Spectral Hamiltonian Monte Carlo AAAI 2019 Statistical Model Aggregation via Parameter Matching NeurIPS 2019 Stein Variational Gradient Descent With Matrix-Valued Kernels NeurIPS 2019 Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction NeurIPS 2019 Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond NeurIPS 2019 Striking the Right Balance With Uncertainty CVPR 2019 Structured Bayesian Networks: From Inference to Learning with Routes AAAI 2019 Subspace Inference for Bayesian Deep Learning UAI 2019 Switching Linear Dynamics for Variational Bayes Filtering ICML 2019 Tensorial Change Analysis Using Probabilistic Tensor Regression AAAI 2019 Tensor Monte Carlo: Particle Methods for the GPU era NeurIPS 2019 The continuous Bernoulli: fixing a pervasive error in variational autoencoders NeurIPS 2019