Gaussian Processes for Big Data

26 September 2013

Papers citing "Gaussian Processes for Big Data"

50 / 604 papers shown

Title
From Local Interactions to Global Operators: Scalable Gaussian Process Operator for Physical Systems Sawan Kumar Tapas Tripura R. Nayek S. Chakraborty 24 0 0 18 Jun 2025
Accurate and Uncertainty-Aware Multi-Task Prediction of HEA Properties Using Prior-Guided Deep Gaussian Processes Sk Md Ahnaf Akif Alvi Mrinalini Mulukutla Nicolas Flores Danial Khatamsaz Jan Janssen Danny Perez D. Allaire V. Attari Raymundo Arroyave AI4CE 15 0 0 13 Jun 2025
Physically-informed change-point kernels for structural dynamics D. J. Pitchforth M. R. Jones S. Gibson E. Cross 27 0 0 13 Jun 2025
Scalable Gaussian Processes with Latent Kronecker Structure Jihao Andreas Lin Sebastian Ament Maximilian Balandat David Eriksson José Miguel Hernández-Lobato E. Bakshy 22 0 0 07 Jun 2025
On the Usage of Gaussian Process for Efficient Data Valuation Clément Bénesse Patrick Mesana Athénaïs Gautier Sébastien Gambs TDI 86 0 0 04 Jun 2025
STACI: Spatio-Temporal Aleatoric Conformal Inference Brandon Feng David K. Park Xihaier Luo Arantxa Urdangarin Shinjae Yoo Brian J. Reich 29 0 0 27 May 2025
Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling Xinxing Shi Xiaoyu Jiang Mauricio A. Álvarez BDL 112 0 0 22 May 2025
Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project Pratik Rathore Zachary Frangella Sachin Garg Shaghayegh Fazliani Michał Dereziński Madeleine Udell 59 0 0 19 May 2025
Graph and Simplicial Complex Prediction Gaussian Process via the Hodgelet Representations Mathieu Alain So Takao Xiaowen Dong Bastian Rieck Emmanuel Noutahi 75 0 0 16 May 2025
Scaling Gaussian Process Regression with Full Derivative Observations Daniel Huang BDL GP 66 0 0 14 May 2025
Clustering with Communication: A Variational Framework for Single Cell Representation Learning Cong Qi Yuxiao Chen Jie Zhang Wei Zhi DRL 56 0 0 08 May 2025
Gradient-based Sample Selection for Faster Bayesian Optimization Qiyu Wei Haowei Wang Zirui Cao Songhao Wang Richard Allmendinger Mauricio A Álvarez 89 1 0 10 Apr 2025
Adaptive sparse variational approximations for Gaussian process regression Dennis Nieman Botond Szabó 103 0 0 04 Apr 2025
Sparse Gaussian Neural Processes Tommy Rochussen Vincent Fortuin BDL UQCV 198 0 0 02 Apr 2025
Preconditioned Additive Gaussian Processes with Fourier Acceleration Theresa Wagner Tianshi Xu Franziska Nestler Yuanzhe Xi Martin Stoll 87 1 0 01 Apr 2025
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems Zhidi Lin Ying Li Feng Yin Juan Maroñas Alexandre Thiéry 164 0 0 24 Mar 2025
Stochastic Poisson Surface Reconstruction with One Solve using Geometric Gaussian Processes Sidhanth Holalkere David S. Bindel Silvia Sellán Alexander Terenin 114 0 0 24 Mar 2025
Exploiting Concavity Information in Gaussian Process Contextual Bandit Optimization Kevin Li Eric Laber 88 0 0 13 Mar 2025
Efficient dynamic modal load reconstruction using physics-informed Gaussian processes based on frequency-sparse Fourier basis functions Gledson Rodrigo Tondo I. Kavrakov Guido Morgenthal 87 2 0 13 Mar 2025
Massively Parallel Expectation Maximization For Approximate Posteriors Thomas Heap Sam Bowyer Laurence Aitchison 71 0 0 11 Mar 2025
Mixed Likelihood Variational Gaussian Processes Kaiwen Wu Craig Sanders Benjamin Letham Phillip Guan 109 0 0 06 Mar 2025
HiGP: A high-performance Python package for Gaussian Process Hua Huang Tianshi Xu Yuanzhe Xi Edmond Chow GP 102 4 0 04 Mar 2025
Shared Stochastic Gaussian Process Latent Variable Models: A Multi-modal Generative Model for Quasar Spectra Vidhi Lalchand Anna-Christina Eilers 108 0 0 27 Feb 2025
Revisiting Kernel Attention with Correlated Gaussian Process Representation Long Minh Bui Tho Tran Huu Duy-Tung Dinh T. Nguyen Trong Nghia Hoang 127 2 0 27 Feb 2025
Koopman-Equivariant Gaussian Processes Petar Bevanda Max Beier Armin Lederer A. Capone Stefan Sosnowski Sandra Hirche AI4TS 110 2 0 10 Feb 2025
Decentralized Online Ensembles of Gaussian Processes for Multi-Agent Systems Fernando Llorente Daniel Waxman Petar M. Djurić 76 0 0 07 Feb 2025
Bayesian Adaptive Calibration and Optimal Design Rafael Oliveira Dino Sejdinovic David Howard Edwin Bonilla 238 0 0 20 Jan 2025
Safe Bayesian Optimization for the Control of High-Dimensional Embodied Systems Yunyue Wei Zeji Yi Hongda Li Saraswati Soedarmadji Yanan Sui 99 0 0 31 Dec 2024
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes Yunyue Wei Vincent Zhuang Saraswati Soedarmadji Yanan Sui 406 1 0 31 Dec 2024
Learning from Summarized Data: Gaussian Process Regression with Sample Quasi-Likelihood Yuta Shikuri GP 111 0 0 23 Dec 2024
Bluetooth Low Energy Dataset Using In-Phase and Quadrature Samples for Indoor Localization Samuel G. Leitch Q. Ahmed Ben Van Herbruggen Mathias Baert Jaron Fontaine E. De Poorter A. Shahid P. Lazaridis 71 0 0 02 Dec 2024
Self-supervised cross-modality learning for uncertainty-aware object detection and recognition in applications which lack pre-labelled training data Irum Mehboob Li Sun Alireza Astegarpanah Rustam Stolkin UQCV 80 0 0 05 Nov 2024
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference Jonathan Wenger Kaiwen Wu Philipp Hennig Jacob R. Gardner Geoff Pleiss John P. Cunningham 88 7 0 01 Nov 2024
High-Dimensional Gaussian Process Regression with Soft Kernel Interpolation Chris Camaño Daniel Huang BDL GP 117 1 0 28 Oct 2024
Scalable Random Feature Latent Variable Models Ying Li Zhidi Lin Yuhao Liu Michael Minyi Zhang Pablo Martínez Olmos Petar M. Djurić BDL DRL 99 0 0 23 Oct 2024
Real-time experiment-theory closed-loop interaction for autonomous materials science Haotong Liang Chuangye Wang Heshan Yu Dylan Kirsch Rohit K. Pant A. McDannald A. Kusne Ji-Cheng Zhao Ichiro Takeuchi 52 0 0 22 Oct 2024
Efficient Non-Myopic Layered Bayesian Optimization For Large-Scale Bathymetric Informative Path Planning Alexander Kiessling Ignacio Torroba Chelsea Sidrane Ivan Stenius Jana Tumova John Folkesson 25 1 0 21 Oct 2024
Spectral Representations for Accurate Causal Uncertainty Quantification with Gaussian Processes Hugh Dance Peter Orbanz Arthur Gretton CML 61 1 0 18 Oct 2024
Graph Classification Gaussian Processes via Hodgelet Spectral Features Mathieu Alain So Takao Xiaowen Dong Bastian Rieck Emmanuel Noutahi 159 2 0 14 Oct 2024
Towards Trustworthy Web Attack Detection: An Uncertainty-Aware Ensemble Deep Kernel Learning Model Yonghang Zhou Hongyi Zhu Yidong Chai Yuanchun Jiang Yezheng Liu AAML 111 0 0 10 Oct 2024
Reactive Multi-Robot Navigation in Outdoor Environments Through Uncertainty-Aware Active Learning of Human Preference Landscape Chao Huang Wenshuo Zang Carlo Pinciroli Zhi Jane Li Taposh Banerjee Lili Su Rui Liu 46 0 0 25 Sep 2024
Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient Shaoqi Wang Chunjie Yang Siwei Lou 47 1 0 23 Sep 2024
Physics-Informed Variational State-Space Gaussian Processes Oliver Hamelijnck Arno Solin Theodoros Damoulas 74 1 0 20 Sep 2024
Amortized Variational Inference for Deep Gaussian Processes Qiuxian Meng Yongyou Zhang 37 0 0 18 Sep 2024
Latent mixed-effect models for high-dimensional longitudinal data Priscilla Ong Manuel Haußmann Otto Lönnroth Harri Lähdesmäki 54 0 0 17 Sep 2024
Adaptive Basis Function Selection for Computationally Efficient Predictions Anton Kullberg Frida Marie Viset Isaac Skog Gustaf Hendeby 57 0 0 14 Aug 2024
Information Geometry and Beta Link for Optimizing Sparse Variational Student-t Processes Jian Xu Delu Zeng John Paisley 33 0 0 13 Aug 2024
Exploiting Hankel-Toeplitz Structures for Fast Computation of Kernel Precision Matrices Frida Viset Anton Kullberg Frederiek Wesel Arno Solin 111 0 0 05 Aug 2024
Aggregation Models with Optimal Weights for Distributed Gaussian Processes Liam Hebert Sukhdeep S. Sodhi 62 0 0 01 Aug 2024
Gaussian Processes Sampling with Sparse Grids under Additive Schwarz Preconditioner Haoyuan Chen Rui Tuo 69 0 0 01 Aug 2024