gaussian processes

Physics and Lie symmetry informed Gaussian processes ICML 2024 Principled Preferential Bayesian Optimization ICML 2024 Probabilistic Subgoal Representations for Hierarchical Reinforcement Learning ICML 2024 Actually Sparse Variational Gaussian Processes AISTATS 2023 A Multi-Task Gaussian Process Model for Inferring Time-Varying Treatment Effects in Panel Data AISTATS 2023 Factorial SDE for Multi-Output Gaussian Process Regression AISTATS 2023 Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds JMLR 2023 Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition JMLR 2023 Memory-Based Dual Gaussian Processes for Sequential Learning ICML 2023 Mode-constrained Model-based Reinforcement Learning via Gaussian Processes AISTATS 2023 Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds ICML 2023 Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes ICML 2023 Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes ICML 2023 Variational Sparse Inverse Cholesky Approximation for Latent Gaussian Processes via Double Kullback-Leibler Minimization ICML 2023 Spatial Multivariate Trees for Big Data Bayesian Regression JMLR 2022 A New Representation of Successor Features for Transfer across Dissimilar Environments ICML 2021 Differentially Private Regression and Classification with Sparse Gaussian Processes JMLR 2021 Longitudinal Deep Kernel Gaussian Process Regression AAAI 2021 Objective Bound Conditional Gaussian Process for Bayesian Optimization ICML 2021 SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data ICML 2021 The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning ICML 2021 Conjugate Gradients for Kernel Machines JMLR 2020 Generalized probabilistic principal component analysis of correlated data JMLR 2020 Hierarchical Reinforcement Learning for Pedagogical Policy Induction (Extended Abstract) IJCAI 2020 Learning Constrained Dynamics with Gauss’ Principle adhering Gaussian Processes L4DC 2020