When Gaussian Process Meets Big Data: A Review of Scalable GPs

3 July 2018

Jianfei Cai

Papers citing "When Gaussian Process Meets Big Data: A Review of Scalable GPs"

50 / 68 papers shown

Title
Safety and optimality in learning-based control at low computational cost Dominik Baumann Krzysztof Kowalczyk Cristian R. Rojas K. Tiels Pawel Wachel 34 0 0 12 May 2025
Uncertainty Quantification for Machine Learning in Healthcare: A Survey L. J. L. Lopez Shaza Elsharief Dhiyaa Al Jorf Firas Darwish Congbo Ma Farah E. Shamout 128 0 0 04 May 2025
Geometry-aware Active Learning of Spatiotemporal Dynamic Systems Xizhuo Zhang AI4CE 29 0 0 26 Apr 2025
From Target Tracking to Targeting Track -- Part III: Stochastic Process Modeling and Online Learning Tiancheng Li Jingyuan Wang Guchong Li Dengwei Gao 55 2 0 03 Mar 2025
Machine learning for modelling unstructured grid data in computational physics: a review Sibo Cheng Marc Bocquet Weiping Ding Tobias S. Finn Rui Fu ... Yong Zeng Mingrui Zhang Hao Zhou Kewei Zhu Rossella Arcucci PINN AI4CE 114 0 0 13 Feb 2025
Bayesian Optimization by Kernel Regression and Density-based Exploration Tansheng Zhu Hongyu Zhou Ke Jin Xusheng Xu Qiufan Yuan Lijie Ji 161 0 0 10 Feb 2025
Sparsity-Aware Distributed Learning for Gaussian Processes with Linear Multiple Kernel Richard Cornelius Suwandi Zhidi Lin Feng Yin Zhiguo Wang Sergios Theodoridis GP 67 1 0 17 Jan 2025
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes Yunyue Wei Vincent Zhuang Saraswati Soedarmadji Yanan Sui 153 0 0 31 Dec 2024
Review of Recent Advances in Gaussian Process Regression Methods Chenyi Lyu Xingchi Liu Lyudmila Mihaylova GP 29 3 0 12 Sep 2024
Gaussian Process Upper Confidence Bounds in Distributed Point Target Tracking over Wireless Sensor Networks Xingchi Liu Lyudmila Mihaylova Jemin George T. Pham 40 9 0 11 Sep 2024
Variational Stochastic Gradient Descent for Deep Neural Networks Haotian Chen Anna Kuzina Babak Esmaeili Jakub M. Tomczak 52 0 0 09 Apr 2024
Real-Time Line-Based Room Segmentation and Continuous Euclidean Distance Fields Erik Warberg Adam Miksits Fernando S. Barbosa 3DV 23 0 0 07 Feb 2024
Constraint-Guided Online Data Selection for Scalable Data-Driven Safety Filters in Uncertain Robotic Systems Jason J. Choi F. Castañeda Wonsuhk Jung Bike Zhang Claire J. Tomlin K. Sreenath 35 3 0 23 Nov 2023
Neural Network Methods for Radiation Detectors and Imaging S. Lin S. Ning H. Zhu T. Zhou C. L. Morris S. Clayton M. Cherukara R. T. Chen Z. Wang AI4CE 32 5 0 09 Nov 2023
Resource-Efficient Cooperative Online Scalar Field Mapping via Distributed Sparse Gaussian Process Regression Tianyi Ding Ronghao Zheng Senlin Zhang Meiqin Liu 28 1 0 19 Sep 2023
Distributionally Robust Statistical Verification with Imprecise Neural Networks Souradeep Dutta Michele Caprio Vivian Lin Matthew Cleaveland Kuk Jin Jang I. Ruchkin O. Sokolsky Insup Lee OOD AAML 49 7 0 28 Aug 2023
Learning-based Control for PMSM Using Distributed Gaussian Processes with Optimal Aggregation Strategy Zhenxiao Yin X. Dai Zewen Yang Yang-Wu Shen Georges Hattab Haiying Zhao 33 10 0 26 Jul 2023
Bayesian Optimisation Against Climate Change: Applications and Benchmarks Sigrid Passano Hellan Christopher G. Lucas Nigel H. Goddard 34 1 0 07 Jun 2023
Uniform approximation of common Gaussian process kernels using equispaced Fourier grids A. Barnett P. Greengard M. Rachh 23 7 0 18 May 2023
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial V. Nemani Luca Biggio Xun Huan Zhen Hu Olga Fink Anh Tran Yan Wang Xiaoge Zhang Chao Hu AI4CE 33 75 0 07 May 2023
Mixtures of Gaussian process experts based on kernel stick-breaking processes Yuji Saikai Khue-Dung Dang 17 0 0 26 Apr 2023
Error analysis of regularized trigonometric linear regression with unbounded sampling: a statistical learning viewpoint Anna Scampicchio Elena Arcari M. Zeilinger 17 1 0 16 Mar 2023
Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field Lele Luan Nesar Ramachandra S. Ravi Anindya Bhaduri Piyush Pandita Prasanna Balaprakash M. Anitescu Changjie Sun Liping Wang AI4CE 27 0 0 15 Mar 2023
Sharp Calibrated Gaussian Processes A. Capone Geoff Pleiss Sandra Hirche UQCV 42 4 0 23 Feb 2023
Violation-Aware Contextual Bayesian Optimization for Controller Performance Optimization with Unmodeled Constraints Wenjie Xu Colin N. Jones B. Svetozarevic C. Laughman Ankush Chakrabarty 22 9 0 28 Jan 2023
Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data Zongyu Dai Zhiqi Bu Q. Long 35 4 0 23 Nov 2022
Deep Gaussian Processes for Air Quality Inference Aadesh Desai Eshan Gujarathi Saagar Parikh Sachin Yadav Zeel B Patel Nipun Batra 36 2 0 18 Nov 2022
ET-AL: Entropy-Targeted Active Learning for Bias Mitigation in Materials Data Hengrui Zhang Wei Chen J. Rondinelli Wei Chen AI4CE 19 17 0 15 Nov 2022
Safe and Adaptive Decision-Making for Optimization of Safety-Critical Systems: The ARTEO Algorithm Buse Sibel Korkmaz Marta Zagórowska Mehmet Mercangöz 27 2 0 10 Nov 2022
Atlas: Automate Online Service Configuration in Network Slicing Qiang Liu Nakjung Choi Tao Han 15 7 0 30 Oct 2022
Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture M. Jung He Zhao Joanna Dipnall Belinda Gabbe Lan Du UQCV EDL 57 12 0 06 Oct 2022
Optimal Sensor Placement in Body Surface Networks using Gaussian Processes Emad Alenany Changqing Cheng 11 0 0 07 Sep 2022
Recursively Feasible Probabilistic Safe Online Learning with Control Barrier Functions F. Castañeda Jason J. Choi Wonsuhk Jung Bike Zhang Claire Tomlin K. Sreenath 48 6 0 23 Aug 2022
Data-Driven Stochastic AC-OPF using Gaussian Processes M. Mitrovic A. Lukashevich Petr Vorobev Vladimir Terzija S. Budenny Yury Maximov Deepjoyti Deka 30 4 0 21 Jul 2022
D-CIPHER: Discovery of Closed-form Partial Differential Equations Krzysztof Kacprzyk Zhaozhi Qian M. Schaar AI4CE 27 1 0 21 Jun 2022
Recent Advances in Bayesian Optimization Xilu Wang Yaochu Jin Sebastian Schmitt Markus Olhofer 38 199 0 07 Jun 2022
Forward variable selection enables fast and accurate dynamic system identification with Karhunen-Loève decomposed Gaussian processes Kyle Hayes Michael W. Fouts Ali Baheri D. Mebane 33 0 0 26 May 2022
Fast Gaussian Process Posterior Mean Prediction via Local Cross Validation and Precomputation Alec M. Dunton Benjamin W. Priest Amanda Muyskens GP 32 3 0 22 May 2022
Fully Decentralized, Scalable Gaussian Processes for Multi-Agent Federated Learning George P. Kontoudis D. Stilwell FedML 6 8 0 06 Mar 2022
Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains Haitao Liu Kai Wu Yew-Soon Ong Chao Bian Xiaomo Jiang Xiaofang Wang 19 7 0 25 Feb 2022
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning Sattar Vakili Jonathan Scarlett Da-shan Shiu A. Bernacchia 25 18 0 08 Feb 2022
MeltpoolNet: Melt pool Characteristic Prediction in Metal Additive Manufacturing Using Machine Learning Parand Akbari Francis Ogoke Ning-Yu Kao Kazem Meidani Chun-Yu Yeh William Lee A. Farimani AI4CE 21 86 0 26 Jan 2022
Unboxing the graph: Neural Relational Inference for Mobility Prediction M. Tygesen Francisco Câmara Pereira Filipe Rodrigues AI4TS 20 2 0 25 Jan 2022
Revisiting Memory Efficient Kernel Approximation: An Indefinite Learning Perspective Simon Heilig Maximilian Münch Frank-Michael Schleif 26 1 0 18 Dec 2021
Non-separable Spatio-temporal Graph Kernels via SPDEs A. Nikitin S. T. John Arno Solin Samuel Kaski AI4TS 27 17 0 16 Nov 2021
Contraction rates for sparse variational approximations in Gaussian process regression D. Nieman Botond Szabó Harry Van Zanten 52 17 0 22 Sep 2021
Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes Jongseo Lee Jianxiang Feng Matthias Humt M. Müller Rudolph Triebel UQCV 48 21 0 20 Sep 2021
Scalable Gaussian Processes for Data-Driven Design using Big Data with Categorical Factors Liwei Wang Suraj Yerramilli Akshay Iyer D. Apley Ping Zhu Wei Chen 38 25 0 26 Jun 2021
Deep Gaussian Processes: A Survey Kalvik Jakkala AI4CE GP BDL 26 19 0 21 Jun 2021
Adaptive machine learning for protein engineering B. Hie Kevin Kaichuang Yang 27 80 0 10 Jun 2021