bayesian inference

Sample Adaptive MCMC NeurIPS 2019 Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models NeurIPS 2019 Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers AISTATS 2019 Scalable Collapsed Inference for High-Dimensional Topic Models NAACL 2019 Scalable inference of topic evolution via models for latent geometric structures NeurIPS 2019 Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets ICML 2019 Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap ICML 2019 Semi-Supervised Learning of Decision-Making Models for Human-Robot Collaboration CoRL 2019 Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows AISTATS 2019 Sketching for Latent Dirichlet-Categorical Models AISTATS 2019 Solving Partially Observable Stochastic Games with Public Observations AAAI 2019 Sparse Variational Inference: Bayesian Coresets from Scratch NeurIPS 2019 Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs NeurIPS 2019 SpHMC: Spectral Hamiltonian Monte Carlo AAAI 2019 SpikeCaKe: Semi-Analytic Nonparametric Bayesian Inference for Spike-Spike Neuronal Connectivity AISTATS 2019 Stein Point Markov Chain Monte Carlo ICML 2019 Stein Variational Gradient Descent With Matrix-Valued Kernels NeurIPS 2019 Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction NeurIPS 2019 Stochastic Optimal Control as Approximate Input Inference CoRL 2019 Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates NeurIPS 2019 Streaming Bayesian Inference for Crowdsourced Classification NeurIPS 2019 Structured Variational Inference in Continuous Cox Process Models NeurIPS 2019 Subspace Inference for Bayesian Deep Learning UAI 2019 Switching Linear Dynamics for Variational Bayes Filtering ICML 2019 That’s Mine! Learning Ownership Relations and Norms for Robots AAAI 2019