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gaussian processes

89 papers

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Also known as

GP GPR GPS PGP

Co-occurring keywords

gaussian process (1198) variational inference (2069) bayesian inference (1904) bayesian optimization (623) sparse approximation (76) kernel methods (1096) active learning (1295) markov chain monte carlo (724) expectation propagation (86) bayesian regression (25)

Papers

The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs JMLR 2025
GaussianFormer-2: Probabilistic Gaussian Superposition for Efficient 3D Occupancy Prediction CVPR 2025
HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical Systems NIPS 2024
Large-Scale Gaussian Processes via Alternating Projection AISTATS 2024
No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints AISTATS 2024
Constrained Bayesian Optimization under Partial Observations: Balanced Improvements and Provable Convergence AAAI 2024
Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning AISTATS 2024
Actually Sparse Variational Gaussian Processes AISTATS 2023
Memory-Based Dual Gaussian Processes for Sequential Learning ICML 2023
Variational Sparse Inverse Cholesky Approximation for Latent Gaussian Processes via Double Kullback-Leibler Minimization ICML 2023
Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition JMLR 2023
Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes ICML 2023
Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds ICML 2023
Mode-constrained Model-based Reinforcement Learning via Gaussian Processes AISTATS 2023
Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes ICML 2023
Factorial SDE for Multi-Output Gaussian Process Regression AISTATS 2023
Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds JMLR 2023
A Multi-Task Gaussian Process Model for Inferring Time-Varying Treatment Effects in Panel Data AISTATS 2023
Spatial Multivariate Trees for Big Data Bayesian Regression JMLR 2022
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data ICML 2021
Differentially Private Regression and Classification with Sparse Gaussian Processes JMLR 2021
The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning ICML 2021
Longitudinal Deep Kernel Gaussian Process Regression AAAI 2021
A New Representation of Successor Features for Transfer across Dissimilar Environments ICML 2021
Objective Bound Conditional Gaussian Process for Bayesian Optimization ICML 2021