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gaussian process

1200 papers

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Also known as

GP

Co-occurring keywords

variational inference (2069) bayesian optimization (624) bayesian inference (1907) uncertainty quantification (1393) kernel methods (1097) gaussian processes (89) regret bound (1926) active learning (1301) sparse approximation (76) hyperparameter optimization (406)

Papers

Influenza Forecasting Framework based on Gaussian Processes ICML 2020
Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances ICML 2020
Hierarchical Reinforcement Learning for Pedagogical Policy Induction (Extended Abstract) IJCAI 2020
Multi-task Causal Learning with Gaussian Processes NIPS 2020
Bayesian Probabilistic Numerical Integration with Tree-Based Models NIPS 2020
Time-Bounded Mission Planning in Time-Varying Domains with Semi-MDPs and Gaussian Processes CORL 2020
Unsupervised Deep Shape Descriptor With Point Distribution Learning CVPR 2020
Causal Inference using Gaussian Processes with Structured Latent Confounders ICML 2020
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation IJCAI 2020
Localizing and Amortizing: Efficient Inference for Gaussian Processes ACML 2020
Learning in the Wild with Incremental Skeptical Gaussian Processes IJCAI 2020
Bayesian Optimization using Pseudo-Points IJCAI 2020
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks ICML 2020
Why bigger is not always better: on finite and infinite neural networks ICML 2020
Knowing The What But Not The Where in Bayesian Optimization ICML 2020
Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare AAAI 2020
Semi-parametric Learning of Structured Temporal Point Processes JMLR 2020
Distributionally Ambiguous Optimization for Batch Bayesian Optimization JMLR 2020
The Kalai-Smorodinsky solution for many-objective Bayesian optimization JMLR 2020
Kriging Prediction with Isotropic Matern Correlations: Robustness and Experimental Designs JMLR 2020
Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning NIPS 2020
Efficient Inference for Nonparametric Hawkes Processes Using Auxiliary Latent Variables JMLR 2020
Bayesian Deep Ensembles via the Neural Tangent Kernel NIPS 2020
Convergence of Sparse Variational Inference in Gaussian Processes Regression JMLR 2020
Wide Neural Networks with Bottlenecks are Deep Gaussian Processes JMLR 2020