Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper
Query: Variational learning of inducing variables in sparse Gaussian processes
A unifying view of sparse approximate Gaussian process regression
Bayesian Gaussian Process Latent Variable Model
Bayesian Gaussian Process Models: PAC-Bayesian Generalisation Error Bounds and Sparse Approximations
Variational Inference for Mahalanobis Distance Metrics in Gaussian Process Regression
Sparse Gaussian Processes for Multi-task Learning
Deep Gaussian Processes
Variational Mixture of Gaussian Process Experts
Flexible and efficient Gaussian process models for machine learning
Learning for larger datasets with the Gaussian process latent variable model
Dependent Gaussian Processes
Gaussian Processes for Machine Learning
Projected Subgradient Methods for Learning Sparse Gaussians
Gaussian Processes for Regression
Learning Gaussian processes from multiple tasks
Gaussian Processes for Big Data
Thoughts on Massively Scalable Gaussian Processes
Deep Gaussian Processes for Regression using Approximate Expectation Propagation
Fast hierarchical Gaussian processes
Fast Bayesian inference for nonconjugate Gaussian process regression
On Approximate Inference for Generalized Gaussian Process Models
Convolution Kernels for Natural Language
Tea-induced calmness: Sugar-sweetened tea calms consumers exposed to acute stressor
Ray tracing height fields
Disability studies as a source of critical inquiry for the field of assistive technology
Agent-based demand forecast in multi-echelon supply chain