Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Approximation methods for gaussian process regression
Gaussian Processes for Regression
Gaussian Processes for Machine Learning (GPML) Toolbox
Variational Inference for Mahalanobis Distance Metrics in Gaussian Process Regression
local gaussian process regression for real time online model learning .
Learning Gaussian process kernels via hierarchical Bayes
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo
Automated Variational Inference for Gaussian Process Models
Student-t Processes as Alternatives to Gaussian Processes
Scalable Gaussian Process Classification via Expectation Propagation
Variational Heteroscedastic Gaussian Process Regression
Variational Inference for Uncertainty on the Inputs of Gaussian Process Models
Learning Gaussian processes from multiple tasks
Gaussian Processes for Ordinal Regression
Gaussian Process Networks
Gaussian Process Regression with Heteroscedastic or Non-Gaussian Residuals
Stochastic Differential Equation Methods for Spatio-Temporal Gaussian Process Regression
Bayesian Online Multitask Learning of Gaussian Processes
Neural-net-induced Gaussian process regression for function approximation and PDE solution
Probabilistic Programming with Gaussian Process Memoization
Computationally Efficient Bayesian Learning of Gaussian Process State Space Models
20-Gbps optical LiFi transport system.
A Practical Bayesian Framework for Backpropagation Networks
Incremental Algorithms for Hierarchical Classification
Adversarial Stain Transfer for Histopathology Image Analysis
to create or to recall ? neural mechanisms underlying the generation of creative new ideas☆ .