Gaussian Processes for Big Data

26 September 2013

Papers citing "Gaussian Processes for Big Data"

50 / 604 papers shown

Title
Scalable Gaussian Process Classification with Additive Noise for Various Likelihoods Haitao Liu Yew-Soon Ong Ziwei Yu Jianfei Cai Xiaobo Shen 66 3 0 14 Sep 2019
Adversarial $α$ -divergence Minimization for Bayesian Approximate Inference Simón Rodríguez Santana Daniel Hernández-Lobato UQCV BDL 33 7 0 13 Sep 2019
Towards Scalable Gaussian Process Modeling Piyush Pandita Jesper Kristensen Liping Wang 29 3 0 25 Jul 2019
Kernel Mode Decomposition and programmable/interpretable regression networks H. Owhadi C. Scovel G. Yoo 95 5 0 19 Jul 2019
Structured Variational Inference in Unstable Gaussian Process State Space Models Silvan Melchior Sebastian Curi Felix Berkenkamp Andreas Krause 89 4 0 16 Jul 2019
Memory of Motion for Warm-starting Trajectory Optimization Teguh Santoso Lembono Antonio Paolillo Emmanuel Pignat Sylvain Calinon 82 45 0 02 Jul 2019
Multi-task Learning for Aggregated Data using Gaussian Processes F. Yousefi M. Smith Mauricio A. Alvarez FedML 72 34 0 22 Jun 2019
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes Creighton Heaukulani Mark van der Wilk BDL 89 15 0 22 Jun 2019
Multi-resolution Multi-task Gaussian Processes Oliver Hamelijnck Theodoros Damoulas Kangrui Wang Mark Girolami 64 38 0 19 Jun 2019
Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances Csaba Tóth Harald Oberhauser 48 9 0 19 Jun 2019
A Survey of Optimization Methods from a Machine Learning Perspective Shiliang Sun Zehui Cao Han Zhu Jing Zhao 88 566 0 17 Jun 2019
Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models Alessandro Davide Ialongo Mark van der Wilk J. Hensman C. Rasmussen 79 30 0 13 Jun 2019
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations Wu Lin Mohammad Emtiyaz Khan Mark Schmidt BDL 111 71 0 07 Jun 2019
Physics Enhanced Data-Driven Models with Variational Gaussian Processes Daniel L. Marino Milos Manic 30 3 0 05 Jun 2019
Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel Xin Qiu Elliot Meyerson Risto Miikkulainen UQCV 90 54 0 03 Jun 2019
Neural Likelihoods for Multi-Output Gaussian Processes M. Jankowiak Jacob R. Gardner UQCV BDL 58 3 0 31 May 2019
Non-linear Multitask Learning with Deep Gaussian Processes Ayman Boustati Theodoros Damoulas R. Savage BDL 48 6 0 29 May 2019
Lifelong Bayesian Optimization Yao Zhang James Jordon Ahmed Alaa M. Schaar 123 11 0 29 May 2019
Recursive Estimation for Sparse Gaussian Process Regression Manuel Schürch Dario Azzimonti A. Benavoli Marco Zaffalon 65 33 0 28 May 2019
Scalable Training of Inference Networks for Gaussian-Process Models Jiaxin Shi Mohammad Emtiyaz Khan Jun Zhu BDL 49 18 0 27 May 2019
Sequential Gaussian Processes for Online Learning of Nonstationary Functions M. Zhang Bianca Dumitrascu Sinead Williamson Barbara E. Engelhardt 66 8 0 24 May 2019
Learning spectrograms with convolutional spectral kernels Zheyan Shen Markus Heinonen Samuel Kaski 64 9 0 23 May 2019
Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation Théo Galy-Fajou F. Wenzel Christian Donner Manfred Opper 62 30 0 23 May 2019
Online Anomaly Detection with Sparse Gaussian Processes Jingjing Fei Shiliang Sun AI4TS 57 21 0 14 May 2019
Deep Gaussian Processes with Importance-Weighted Variational Inference Hugh Salimbeni Vincent Dutordoir J. Hensman M. Deisenroth BDL 99 44 0 14 May 2019
Adaptive surrogate models for parametric studies J. Fuhg 43 8 0 12 May 2019
Bayesian Optimization using Deep Gaussian Processes Ali Hebbal Loïc Brevault M. Balesdent El-Ghazali Talbi N. Melab GP 95 70 0 07 May 2019
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features Arno Solin Manon Kok 74 23 0 10 Apr 2019
Robust Deep Gaussian Processes Jeremias Knoblauch GP 69 17 0 04 Apr 2019
A Machine Learning approach to Risk Minimisation in Electricity Markets with Coregionalized Sparse Gaussian Processes Daniel Poh Stephen J. Roberts Martin Tegnér 19 0 0 22 Mar 2019
Exact Gaussian Processes on a Million Data Points Ke Alexander Wang Geoff Pleiss Jacob R. Gardner Stephen Tyree Kilian Q. Weinberger A. Wilson GP 69 231 0 19 Mar 2019
Deep Gaussian Processes for Multi-fidelity Modeling Kurt Cutajar Mark Pullin Andreas C. Damianou Neil D. Lawrence Javier I. González AI4CE 75 110 0 18 Mar 2019
Functional Variational Bayesian Neural Networks Shengyang Sun Guodong Zhang Jiaxin Shi Roger C. Grosse BDL 83 240 0 14 Mar 2019
Rates of Convergence for Sparse Variational Gaussian Process Regression David R. Burt C. Rasmussen Mark van der Wilk 76 155 0 08 Mar 2019
Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning Evgenii Tsymbalov Sergei Makarychev Alexander Shapeev Maxim Panov BDL UQCV 52 21 0 27 Feb 2019
Bayesian Image Classification with Deep Convolutional Gaussian Processes Vincent Dutordoir Mark van der Wilk A. Artemev J. Hensman UQCV BDL 161 32 0 15 Feb 2019
Hybrid Models with Deep and Invertible Features Eric T. Nalisnick Akihiro Matsukawa Yee Whye Teh Dilan Görür Balaji Lakshminarayanan BDL DRL 119 99 0 07 Feb 2019
End-to-End Probabilistic Inference for Nonstationary Audio Analysis William J. Wilkinson Michael Riis Andersen Joshua D. Reiss D. Stowell Arno Solin 67 5 0 31 Jan 2019
Functional Regularisation for Continual Learning with Gaussian Processes Michalis K. Titsias Jonathan Richard Schwarz A. G. Matthews Razvan Pascanu Yee Whye Teh CLL BDL 77 187 0 31 Jan 2019
On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis K. Hayashi Masaaki Imaizumi Yuichi Yoshida 55 12 0 28 Jan 2019
Variational bridge constructs for approximate Gaussian process regression W. Ward Mauricio A. Alvarez 28 1 0 07 Jan 2019
Learning Nonlinear State Space Models with Hamiltonian Sequential Monte Carlo Sampler Duo Xu 64 2 0 03 Jan 2019
Non-Factorised Variational Inference in Dynamical Systems Alessandro Davide Ialongo Mark van der Wilk J. Hensman C. Rasmussen 79 6 0 14 Dec 2018
Bayesian Layers: A Module for Neural Network Uncertainty Dustin Tran Michael W. Dusenberry Mark van der Wilk Danijar Hafner UQCV BDL 131 124 0 10 Dec 2018
Partitioned Variational Inference: A unified framework encompassing federated and continual learning T. Bui Cuong V Nguyen S. Swaroop Richard Turner FedML 91 56 0 27 Nov 2018
Mixed Likelihood Gaussian Process Latent Variable Model Samuel Murray Hedvig Kjellström 18 4 0 19 Nov 2018
Infinite-Horizon Gaussian Processes Arno Solin J. Hensman Richard Turner 65 28 0 15 Nov 2018
Large-scale Heteroscedastic Regression via Gaussian Process Haitao Liu Yew-Soon Ong Jianfei Cai BDL 83 26 0 03 Nov 2018
Understanding and Comparing Scalable Gaussian Process Regression for Big Data Haitao Liu Jianfei Cai Yew-Soon Ong Yi Wang 75 26 0 03 Nov 2018
Gaussian Process Conditional Density Estimation Vincent Dutordoir Hugh Salimbeni M. Deisenroth J. Hensman 161 52 0 30 Oct 2018