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Gaussian Processes

570 papers

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Papers

Efficient Bayesian Inference of Sigmoidal Gaussian Cox Processes JMLR 2018
Differential networking with path weights in Gaussian trees PGM 2018
Identification of Gaussian Process State Space Models NIPS 2017
Spectral Mixture Kernels for Multi-Output Gaussian Processes NIPS 2017
Cross-Spectral Factor Analysis NIPS 2017
Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs NIPS 2017
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes NIPS 2017
Linearly constrained Gaussian processes NIPS 2017
Safe Model-based Reinforcement Learning with Stability Guarantees NIPS 2017
Targeting EEG/LFP Synchrony with Neural Nets NIPS 2017
Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes NIPS 2017
Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models NIPS 2017
Doubly Stochastic Variational Inference for Deep Gaussian Processes NIPS 2017
Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks NIPS 2017
GP CaKe: Effective brain connectivity with causal kernels NIPS 2017
Gaussian process based nonlinear latent structure discovery in multivariate spike train data NIPS 2017
Non-Stationary Spectral Kernels NIPS 2017
Streaming Sparse Gaussian Process Approximations NIPS 2017
Variational Inference for Gaussian Process Models with Linear Complexity NIPS 2017
Active Incremental Learning of Robot Movement Primitives CORL 2017
Extending Model-based Policy Gradients for Robots in Heteroscedastic Environments CORL 2017
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings ACML 2017
Gray-box Inference for Structured Gaussian Process Models AISTATS 2017
Variational Bayesian Multiple Instance Learning With Gaussian Processes CVPR 2017
Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control ICML 2017