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Gaussian Processes

570 papers

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Papers

Algorithmic Linearly Constrained Gaussian Processes NIPS 2018
Safe Active Learning for Time-Series Modeling with Gaussian Processes NIPS 2018
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification NIPS 2018
Infinite-Horizon Gaussian Processes NIPS 2018
Scaling Gaussian Process Regression with Derivatives NIPS 2018
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds NIPS 2018
Feature-correlation-aware Gaussian Process Latent Variable Model ACML 2018
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models AISTATS 2018
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition AISTATS 2018
Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling AISTATS 2018
Scalable Generalized Dynamic Topic Models AISTATS 2018
A Prior-Less Method for Multi-Face Tracking in Unconstrained Videos CVPR 2018
Wrapped Gaussian Process Regression on Riemannian Manifolds CVPR 2018
Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design ICML 2018
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning ICML 2018
Differentially Private Database Release via Kernel Mean Embeddings ICML 2018
Large-Scale Cox Process Inference using Variational Fourier Features ICML 2018
State Space Gaussian Processes with Non-Gaussian Likelihood ICML 2018
Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches ICML 2018
Constant-Time Predictive Distributions for Gaussian Processes ICML 2018
Differentiable Compositional Kernel Learning for Gaussian Processes ICML 2018
Gaussian Process Neural Networks for Speech Recognition INTERSPEECH 2018
Variational Fourier Features for Gaussian Processes JMLR 2018
Patchwork Kriging for Large-scale Gaussian Process Regression JMLR 2018
How Deep Are Deep Gaussian Processes? JMLR 2018