Gaussian Processes

Longitudinal Deep Kernel Gaussian Process Regression AAAI 2021 Marginalised Gaussian Processes with Nested Sampling NeurIPS 2021 Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis JMLR 2021 Nonparametric Decomposition of Sparse Tensors ICML 2021 Objective Bound Conditional Gaussian Process for Bayesian Optimization ICML 2021 On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization ICML 2021 On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes ICML 2021 Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search ICML 2021 Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression AAAI 2021 Probabilistic robust linear quadratic regulators with Gaussian processes L4DC 2021 Raven's Progressive Matrices Completion with Latent Gaussian Process Priors AAAI 2021 Scalable gradient matching based on state space Gaussian Processes ACML 2021 Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition ICML 2021 SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data ICML 2021 Sparse within Sparse Gaussian Processes using Neighbor Information ICML 2021 Spatio-Temporal Variational Gaussian Processes NeurIPS 2021 Structure-Aware Random Fourier Kernel for Graphs NeurIPS 2021 The Impact of Data on the Stability of Learning-Based Control L4DC 2021 Uncertain-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric L4DC 2021 Value-at-Risk Optimization with Gaussian Processes ICML 2021 Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels NeurIPS 2021 Bayesian Image Classification with Deep Convolutional Gaussian Processes AISTATS 2020 Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances ICML 2020 Bayesian Optimization using Pseudo-Points IJCAI 2020 Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties NeurIPS 2020