Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper.
Query: Introduction to Gaussian processes
Flexible and efficient Gaussian process models for machine learning
Sparse Gaussian Processes using Pseudo-inputs
Parameter space exploration with Gaussian process trees
Scalable Gaussian Process Classification via Expectation Propagation
Gaussian Process Optimization with Mutual Information
Generalized Product of Experts for Automatic and Principled Fusion of Gaussian Process Predictions
Gaussian Process Regression Networks
Computationally efficient convolved multiple output gaussian processes
Gaussian Process Training with Input Noise
Gaussian Processes for Classification: Mean-Field Algorithms
Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC
Gaussian predictive process models for large spatial data sets
Bayesian classification with Gaussian processes
Gaussian Process Dynamical Models
Fast forward selection to speed up sparse gaussian process regression
pyGPs: a Python library for Gaussian process regression and classification
Variational learning of inducing variables in sparse Gaussian processes
Variational Gaussian Process Dynamical Systems
Deep Convolutional Networks as shallow Gaussian Processes
Variational Inference for Mahalanobis Distance Metrics in Gaussian Process Regression
Sparse Gaussian Processes using Pseudo-inputs
A Linear Speedup Analysis of Distributed Deep Learning with Sparse and Quantized Communication
Speech Disfluency-dependent Amygdala Activity in Adults Who Stutter: Neuroimaging of Interpersonal Communication in MRI Scanner Environment
Sales forecasting using extreme learning machine with applications in fashion retailing
A Review on Moving Object Detection and Tracking