Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
GP-UKF: Unscented kalman filters with Gaussian process prediction and observation models
Bayesian classification with Gaussian processes
A Review of the Bayesian Occupancy Filter
Progressive Gaussian filtering using explicit likelihoods
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data
Information Gain-based Exploration Using Rao-Blackwellized Particle Filters
Deep Gaussian Processes for Regression using Approximate Expectation Propagation
On Approximate Inference for Generalized Gaussian Process Models
Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors
Bayesian Gaussian Process Classification with the EM-EP Algorithm
Dependent Gaussian Processes
Gaussian filters for nonlinear filtering problems
Flexible and efficient Gaussian process models for machine learning
Novel approach to nonlinear/non-Gaussian Bayesian state estimation
local gaussian process regression for real time online model learning .
DRAFT — — — An introduction to particle filters
Variational Bayesian Inference : Algorithms for Sparse Gaussian Processes and Theoretical Bounds
Prediction With Gaussian Processes: From Linear Regression To Linear Prediction And Beyond
Gaussian Processes for Machine Learning
Variational Inference for Uncertainty on the Inputs of Gaussian Process Models
Reference metadata extraction using a hierarchical knowledge representation framework
personas , participatory design and product development : an infrastructure for engagement .
Distributed Cooperative Control and Stability Analysis of Multiple DC Electric Springs in a DC Microgrid
Learning the Kernel Matrix with Semi-Definite Programming
Studying the History of Ideas Using Topic Models