Gaussian Processes for Big Data

26 September 2013

Papers citing "Gaussian Processes for Big Data"

50 / 604 papers shown

Title
PAGP: A physics-assisted Gaussian process framework with active learning for forward and inverse problems of partial differential equations Jiahao Zhang Shiqi Zhang Guang Lin 83 3 0 06 Apr 2022
Hybrid Transfer in Deep Reinforcement Learning for Ads Allocation Zehua Wang Guogang Liao Xiaowen Shi Xiaoxu Wu Wei Shen Bingqin Zhu Yongkang Wang Xingxing Wang Dong Wang 54 5 0 02 Apr 2022
Safe Active Learning for Multi-Output Gaussian Processes Cen-You Li Barbara Rakitsch Christoph Zimmer UQCV 136 18 0 28 Mar 2022
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders Samuel Stanton Wesley J. Maddox Nate Gruver Phillip M. Maffettone E. Delaney Peyton Greenside A. Wilson BDL 77 98 0 23 Mar 2022
Fully-probabilistic Terrain Modelling with Stochastic Variational Gaussian Process Maps Ignacio Torroba Christopher Iliffe Sprague John Folkesson 53 1 0 21 Mar 2022
Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback T. Hoang Anoop Deoras Tong Zhao Jin Li George Karypis FedML 62 5 0 18 Mar 2022
Fully Decentralized, Scalable Gaussian Processes for Multi-Agent Federated Learning George P. Kontoudis D. Stilwell FedML 84 8 0 06 Mar 2022
Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes Felix Jimenez Matthias Katzfuss 71 10 0 02 Mar 2022
Learning Conditional Variational Autoencoders with Missing Covariates S. Ramchandran Gleb Tikhonov Otto Lönnroth Pekka Tiikkainen Harri Lähdesmäki CML 72 19 0 02 Mar 2022
Video is All You Need: Attacking PPG-based Biometric Authentication Lin Li Chao Chen Lei Pan Jun Zhang Yang Xiang AAML 42 13 0 02 Mar 2022
Generalised Gaussian Process Latent Variable Models (GPLVM) with Stochastic Variational Inference V. Lalchand Aditya Ravuri Neil D. Lawrence GP VLM 34 6 0 25 Feb 2022
Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains Haitao Liu Kai Wu Yew-Soon Ong Chao Bian Xiaomo Jiang Xiaofang Wang 80 8 0 25 Feb 2022
AutoIP: A United Framework to Integrate Physics into Gaussian Processes D. Long Ziyi Wang Aditi S. Krishnapriyan Robert M. Kirby Shandian Zhe Michael W. Mahoney AI4CE 95 15 0 24 Feb 2022
Partitioned Variational Inference: A Framework for Probabilistic Federated Learning Matthew Ashman T. Bui Cuong V Nguyen Efstratios Markou Adrian Weller S. Swaroop Richard Turner FedML 65 14 0 24 Feb 2022
Bayesian Model Selection, the Marginal Likelihood, and Generalization Sanae Lotfi Pavel Izmailov Gregory W. Benton Micah Goldblum A. Wilson UQCV BDL 153 58 0 23 Feb 2022
Adaptive Cholesky Gaussian Processes Simon Bartels Kristoffer Stensbo-Smidt Pablo Moreno-Muñoz Wouter Boomsma J. Frellsen Søren Hauberg 95 3 0 22 Feb 2022
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning Sattar Vakili Jonathan Scarlett Da-shan Shiu A. Bernacchia 90 19 0 08 Feb 2022
Theoretical characterization of uncertainty in high-dimensional linear classification Lucas Clarté Bruno Loureiro Florent Krzakala Lenka Zdeborová 91 21 0 07 Feb 2022
Incorporating Sum Constraints into Multitask Gaussian Processes Philipp Pilar Carl Jidling Thomas B. Schon Niklas Wahlström TPM 58 3 0 03 Feb 2022
Variational Nearest Neighbor Gaussian Process Luhuan Wu Geoff Pleiss John P. Cunningham BDL 100 15 0 03 Feb 2022
Giga-scale Kernel Matrix Vector Multiplication on GPU Robert Hu Siu Lun Chau Dino Sejdinovic J. Glaunès 115 2 0 02 Feb 2022
Local Latent Space Bayesian Optimization over Structured Inputs Natalie Maus Haydn Thomas Jones Juston Moore Matt J. Kusner John Bradshaw Jacob R. Gardner BDL 120 72 0 28 Jan 2022
Online Time Series Anomaly Detection with State Space Gaussian Processes Christian Bock Franccois-Xavier Aubet Jan Gasthaus Andrey Kan Ming Chen Laurent Callot AI4TS 67 8 0 18 Jan 2022
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression Giacomo Meanti Luigi Carratino Ernesto De Vito Lorenzo Rosasco 61 13 0 17 Jan 2022
When are Iterative Gaussian Processes Reliably Accurate? Wesley J. Maddox Sanyam Kapoor A. Wilson 74 10 0 31 Dec 2021
Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations Srinivas Anumasa P. K. Srijith OOD UQCV BDL 81 11 0 23 Dec 2021
Correlated Product of Experts for Sparse Gaussian Process Regression Manuel Schürch Dario Azzimonti A. Benavoli Marco Zaffalon 43 12 0 17 Dec 2021
Comparing Machine Learning and Interpolation Methods for Loop-Level Calculations Ibrahim Chahrour J. Wells 93 12 0 29 Nov 2021
Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity Modeling Xubo Yue Raed Al Kontar FedML 138 9 0 28 Nov 2021
Bayesian Learning via Neural Schrödinger-Föllmer Flows Francisco Vargas Andrius Ovsianas David Fernandes Mark Girolami Neil D. Lawrence Nikolas Nusken BDL 150 49 0 20 Nov 2021
Gaussian Process Inference Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits Hao Chen Lili Zheng Raed Al Kontar Garvesh Raskutti 86 3 0 19 Nov 2021
BOiLS: Bayesian Optimisation for Logic Synthesis Antoine Grosnit C. Malherbe Rasul Tutunov Xingchen Wan Jun Wang H. Ammar 113 32 0 11 Nov 2021
Searching in the Forest for Local Bayesian Optimization Difan Deng Marius Lindauer 40 2 0 10 Nov 2021
Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes Hugh Dance Brooks Paige GP 74 10 0 08 Nov 2021
Dual Parameterization of Sparse Variational Gaussian Processes Vincent Adam Paul E. Chang Mohammad Emtiyaz Khan Arno Solin 97 23 0 05 Nov 2021
Spatio-Temporal Variational Gaussian Processes Oliver Hamelijnck William J. Wilkinson Niki A. Loppi Arno Solin Theodoros Damoulas AI4TS 80 35 0 02 Nov 2021
Aligned Multi-Task Gaussian Process O. Mikheeva Ieva Kazlauskaite Adam Hartshorne Hedvig Kjellström Carl Henrik Ek Neill D. F. Campbell AI4TS 69 2 0 29 Oct 2021
Conditioning Sparse Variational Gaussian Processes for Online Decision-making Wesley J. Maddox Samuel Stanton A. Wilson 81 32 0 28 Oct 2021
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels M. Hutchinson Alexander Terenin Viacheslav Borovitskiy So Takao Yee Whye Teh M. Deisenroth 78 22 0 27 Oct 2021
Modular Gaussian Processes for Transfer Learning P. Moreno-Muñoz Antonio Artés-Rodríguez Mauricio A. Alvarez 46 4 0 26 Oct 2021
Variational Gaussian Processes: A Functional Analysis View Veit Wild George Wynne GP 80 5 0 25 Oct 2021
Variational Bayesian Approximation of Inverse Problems using Sparse Precision Matrices Jan Povala Ieva Kazlauskaite Eky Febrianto F. Cirak Mark Girolami 91 23 0 22 Oct 2021
Function-space Inference with Sparse Implicit Processes Simón Rodríguez Santana B. Zaldívar Daniel Hernández-Lobato 63 12 0 14 Oct 2021
Nonnegative spatial factorization F. W. Townes Barbara E. Engelhardt 42 11 0 12 Oct 2021
Scaling Bayesian Optimization With Game Theory L. Mathesen G. Pedrielli R. L. Smith 93 1 0 07 Oct 2021
Non-stationary Gaussian process discriminant analysis with variable selection for high-dimensional functional data Weichang Yu S. Wade H. Bondell Lamiae Azizi 46 4 0 29 Sep 2021
Gaussian Processes to speed up MCMC with automatic exploratory-exploitation effect A. Benavoli J. Wyse Arthur J. White GP 20 0 0 28 Sep 2021
Molecular Energy Learning Using Alternative Blackbox Matrix-Matrix Multiplication Algorithm for Exact Gaussian Process Jiace Sun Lixue Cheng Thomas F. Miller 59 3 0 20 Sep 2021
Scalable Multi-Task Gaussian Processes with Neural Embedding of Coregionalization Haitao Liu Jiaqi Ding Xinyu Xie Xiaomo Jiang Yusong Zhao Xiaofang Wang BDL 62 17 0 20 Sep 2021
Self-explaining variational posterior distributions for Gaussian Process models Sarem Seitz BDL 31 0 0 08 Sep 2021