Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Asymmetric Transfer Learning with Deep Gaussian Processes
Multi-task Gaussian Process Prediction
Bayesian Gaussian Process Models: PAC-Bayesian Generalisation Error Bounds and Sparse Approximations
Fast Bayesian inference for nonconjugate Gaussian process regression
On Approximate Inference for Generalized Gaussian Process Models
Gaussian Processes for Machine Learning (GPML) Toolbox
Variational Inference for Uncertainty on the Inputs of Gaussian Process Models
local gaussian process regression for real time online model learning .
One-shot learning of object categories using dependent Gaussian processes
Bayesian classification with Gaussian processes
Projected Subgradient Methods for Learning Sparse Gaussians
Spatio-Temporal Learning With the Online Finite and Infinite Echo-State Gaussian Processes
appendix of : inverse reinforcement learning via deep gaussian process .
Domain Invariant Transfer Kernel Learning
Contextual Gaussian Process Bandit Optimization
Gaussian Processes for Regression
Robust and Efficient Transfer Learning with Hidden-Parameter Markov Decision Processes
Variational Inference for Mahalanobis Distance Metrics in Gaussian Process Regression
Variational Mixture of Gaussian Process Experts
Student-t Processes as Alternatives to Gaussian Processes
Bayesian Modeling with Gaussian Processes using the GPstuff Toolbox
Dynamic Time-Dependent Route Planning in Road Networks with User Preferences
Real-world Multi-object, Multi-grasp Detection
Alleviating Data Sparsity for Twitter Sentiment Analysis
Finding Linear Structure in Large Datasets with Scalable Canonical Correlation Analysis
Learning Multiple Tasks with Kernel Methods