Gaussian Processes for Big Data

26 September 2013

Papers citing "Gaussian Processes for Big Data"

50 / 604 papers shown

Title
Sparse Gaussian Process Audio Source Separation Using Spectrum Priors in the Time-Domain Pablo A. Alvarado Mauricio A. Alvarez D. Stowell 34 7 0 30 Oct 2018
Scaling Gaussian Process Regression with Derivatives David Eriksson Kun Dong E. Lee D. Bindel A. Wilson GP 63 76 0 29 Oct 2018
Gaussian Process Prior Variational Autoencoders F. P. Casale Adrian Dalca Luca Saglietti Jennifer Listgarten Nicolò Fusi BDL CML 75 139 0 28 Oct 2018
Scalable Gaussian Processes on Discrete Domains Vincent Fortuin Gideon Dresdner Heiko Strathmann Gunnar Rätsch BDL 116 3 0 24 Oct 2018
Data Association with Gaussian Processes Markus Kaiser Clemens Otte Thomas Runkler Carl Henrik Ek 28 0 0 16 Oct 2018
Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models Kaspar Märtens Kieran R. Campbell C. Yau 30 0 0 16 Oct 2018
Deep learning with differential Gaussian process flows Pashupati Hegde Markus Heinonen Harri Lähdesmäki Samuel Kaski BDL 95 42 0 09 Oct 2018
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration Jacob R. Gardner Geoff Pleiss D. Bindel Kilian Q. Weinberger A. Wilson GP 154 1,106 0 28 Sep 2018
Orthogonally Decoupled Variational Gaussian Processes Hugh Salimbeni Ching-An Cheng Byron Boots M. Deisenroth 82 43 0 24 Sep 2018
Learning Deep Mixtures of Gaussian Process Experts Using Sum-Product Networks Martin Trapp Robert Peharz C. Rasmussen Franz Pernkopf TPM GP 54 7 0 12 Sep 2018
Non-Parametric Variational Inference with Graph Convolutional Networks for Gaussian Processes Linfeng Liu Liping Liu BDL 30 0 0 08 Sep 2018
Learning Invariances using the Marginal Likelihood Mark van der Wilk Matthias Bauer S. T. John J. Hensman 97 86 0 16 Aug 2018
Machine Learning of Space-Fractional Differential Equations Mamikon A. Gulian M. Raissi P. Perdikaris George Karniadakis 109 47 0 02 Aug 2018
Compressible Spectral Mixture Kernels with Sparse Dependency Structures for Gaussian Processes Kai Chen Yijue Dai Feng Yin Shuguang Cui Sergios Theodoridis 53 3 0 01 Aug 2018
Noise Contrastive Priors for Functional Uncertainty Danijar Hafner Dustin Tran Timothy Lillicrap A. Irpan James Davidson AAML BDL UQCV 150 74 0 24 Jul 2018
Composite likelihood estimation for a gaussian process under fixed domain asymptotics François Bachoc M. Bevilacqua D. Velandia 58 12 0 24 Jul 2018
Meta-Learning Priors for Efficient Online Bayesian Regression James Harrison Apoorva Sharma Marco Pavone BDL 91 102 0 24 Jul 2018
Learning Stochastic Differential Equations With Gaussian Processes Without Gradient Matching Çağatay Yıldız Markus Heinonen Jukka Intosalmi Henrik Mannerstrom Harri Lähdesmäki DiffM 71 39 0 16 Jul 2018
Fully Scalable Gaussian Processes using Subspace Inducing Inputs A. Panos P. Dellaportas Michalis K. Titsias 57 12 0 06 Jul 2018
When Gaussian Process Meets Big Data: A Review of Scalable GPs Haitao Liu Yew-Soon Ong Xiaobo Shen Jianfei Cai GP 144 699 0 03 Jul 2018
Spatiotemporal Prediction of Ambulance Demand using Gaussian Process Regression Seth Nabarro Tristan Fletcher John Shawe-Taylor GP 16 2 0 28 Jun 2018
Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees Jonathan H. Huggins Trevor Campbell Mikolaj Kasprzak Tamara Broderick 95 15 0 26 Jun 2018
Neural-net-induced Gaussian process regression for function approximation and PDE solution G. Pang Liu Yang George Karniadakis 78 73 0 22 Jun 2018
Variational Implicit Processes Chao Ma Yingzhen Li José Miguel Hernández-Lobato BDL 121 70 0 06 Jun 2018
Deep Gaussian Processes with Convolutional Kernels Vinayak Kumar Vaibhav Singh P. K. Srijith Andreas C. Damianou BDL GP 109 30 0 05 Jun 2018
Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression Haitao Liu Jianfei Cai Yi Wang Yew-Soon Ong 81 84 0 03 Jun 2018
Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems T. Hoang Q. Hoang K. H. Low Jonathan P. How 53 7 0 23 May 2018
Variational Learning on Aggregate Outputs with Gaussian Processes H. Law Dino Sejdinovic E. Cameron T. Lucas Seth Flaxman K. Battle Kenji Fukumizu 56 38 0 22 May 2018
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation Manuel Haussmann Fred Hamprecht M. Kandemir BDL 72 6 0 19 May 2018
Heterogeneous Multi-output Gaussian Process Prediction P. Moreno-Muñoz Antonio Artés-Rodríguez Mauricio A. Alvarez 69 72 0 19 May 2018
Index Set Fourier Series Features for Approximating Multi-dimensional Periodic Kernels A. Tompkins F. Ramos 52 0 0 14 May 2018
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models Hugh Salimbeni Stefanos Eleftheriadis J. Hensman BDL 91 86 0 24 Mar 2018
Scalable Generalized Dynamic Topic Models P. Jähnichen F. Wenzel Marius Kloft Stephan Mandt BDL 107 40 0 21 Mar 2018
Meta Reinforcement Learning with Latent Variable Gaussian Processes Steindór Sæmundsson Katja Hofmann M. Deisenroth BDL OffRL AI4CE 94 142 0 20 Mar 2018
Asymmetric kernel in Gaussian Processes for learning target variance S. Pintea Jan van Gemert A. Smeulders 34 6 0 19 Mar 2018
Constant-Time Predictive Distributions for Gaussian Processes Geoff Pleiss Jacob R. Gardner Kilian Q. Weinberger A. Wilson 82 96 0 16 Mar 2018
Variational zero-inflated Gaussian processes with sparse kernels Pashupati Hegde Markus Heinonen Samuel Kaski 26 5 0 13 Mar 2018
Standing Wave Decomposition Gaussian Process Chi-Ken Lu Scott Cheng-Hsin Yang Patrick Shafto 41 2 0 09 Mar 2018
ADMM-based Networked Stochastic Variational Inference Hamza Anwar Quanyan Zhu BDL 119 3 0 27 Feb 2018
Conditionally Independent Multiresolution Gaussian Processes Jalil Taghia Thomas B. Schon 82 1 0 25 Feb 2018
Product Kernel Interpolation for Scalable Gaussian Processes Jacob R. Gardner Geoff Pleiss Ruihan Wu Kilian Q. Weinberger A. Wilson 82 74 0 24 Feb 2018
The Gaussian Process Autoregressive Regression Model (GPAR) James Requeima Will Tebbutt W. Bruinsma Richard Turner 146 41 0 20 Feb 2018
State Space Gaussian Processes with Non-Gaussian Likelihood H. Nickisch Arno Solin A. Grigorevskiy GP 90 32 0 13 Feb 2018
Few-shot learning of neural networks from scratch by pseudo example optimization Akisato Kimura Zoubin Ghahramani Koh Takeuchi Tomoharu Iwata N. Ueda 94 52 0 08 Feb 2018
Composite Gaussian Processes: Scalable Computation and Performance Analysis Xiuming Liu Dave Zachariah Edith C.H. Ngai 33 0 0 31 Jan 2018
Probabilistic Recurrent State-Space Models Andreas Doerr Christian Daniel Martin Schiegg D. Nguyen-Tuong S. Schaal Marc Toussaint Sebastian Trimpe 109 123 0 31 Jan 2018
Algorithmic Linearly Constrained Gaussian Processes Markus Lange-Hegermann 87 35 0 28 Jan 2018
Variational Inference for Gaussian Process Models with Linear Complexity Ching-An Cheng Byron Boots BDL 76 76 0 28 Nov 2017
Sequential Randomized Matrix Factorization for Gaussian Processes: Efficient Predictions and Hyper-parameter Optimization S. Bopardikar G. Ekladious 24 0 0 19 Nov 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 238 698 0 15 Nov 2017