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Gaussian Processes

568 directly classified papers

Papers per year

Papers

Multi-resolution Multi-task Gaussian Processes NIPS 2019
Exact Gaussian Processes on a Million Data Points NIPS 2019
Bayesian Optimization under Heavy-tailed Payoffs NIPS 2019
Bayesian Layers: A Module for Neural Network Uncertainty NIPS 2019
Safe Exploration for Interactive Machine Learning NIPS 2019
Hyperparameter Learning via Distributional Transfer NIPS 2019
No-Regret Learning in Unknown Games with Correlated Payoffs NIPS 2019
Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes NIPS 2019
Recovering Bandits NIPS 2019
Nonparametric Regressive Point Processes Based on Conditional Gaussian Processes NIPS 2019
Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs NIPS 2019
Band-Limited Gaussian Processes: The Sinc Kernel NIPS 2019
Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control NIPS 2019
Differentially Private Database Release via Kernel Mean Embeddings ICML 2018
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning ICML 2018
Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design ICML 2018
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration NIPS 2018
Differential networking with path weights in Gaussian trees PGM 2018
Scalable Generalized Dynamic Topic Models AISTATS 2018
Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling AISTATS 2018
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition AISTATS 2018
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models AISTATS 2018
Feature-correlation-aware Gaussian Process Latent Variable Model ACML 2018
Variational Fourier Features for Gaussian Processes JMLR 2018
Patchwork Kriging for Large-scale Gaussian Process Regression JMLR 2018