Gaussian Processes for Big Data

26 September 2013

Papers citing "Gaussian Processes for Big Data"

50 / 604 papers shown

Title
Variational Auto-Regressive Gaussian Processes for Continual Learning Sanyam Kapoor Theofanis Karaletsos T. Bui BDL 83 26 0 09 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 73 36 0 09 Jun 2020
PIVEN: A Deep Neural Network for Prediction Intervals with Specific Value Prediction Eli Simhayev Gilad Katz Lior Rokach OOD 51 12 0 09 Jun 2020
Physics Informed Deep Kernel Learning Ziyi Wang Wei W. Xing Robert M. Kirby Shandian Zhe PINN 73 10 0 08 Jun 2020
A Survey of Bayesian Statistical Approaches for Big Data Farzana Jahan Insha Ullah Kerrie Mengersen 102 14 0 08 Jun 2020
Bayesian Hidden Physics Models: Uncertainty Quantification for Discovery of Nonlinear Partial Differential Operators from Data Steven Atkinson 42 8 0 07 Jun 2020
Quadruply Stochastic Gaussian Processes Trefor W. Evans P. Nair GP 48 3 0 04 Jun 2020
Multi-Fidelity Black-Box Optimization for Time-Optimal Quadrotor Maneuvers Gilhyun Ryou E. Tal S. Karaman 93 42 0 03 Jun 2020
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties J. Lindinger David Reeb C. Lippert Barbara Rakitsch BDL UQCV 74 8 0 22 May 2020
Deep Latent-Variable Kernel Learning Haitao Liu Yew-Soon Ong Xiaomo Jiang Xiaofang Wang BDL 59 8 0 18 May 2020
CFDNet: a deep learning-based accelerator for fluid simulations Octavi Obiols-Sales Abhinav Vishnu Nicholas Malaya Aparna Chandramowlishwaran AI4CE 57 152 0 09 May 2020
Active Preference-Based Gaussian Process Regression for Reward Learning Erdem Biyik Nicolas Huynh Mykel J. Kochenderfer Dorsa Sadigh GP 96 110 0 06 May 2020
The ICSCREAM methodology: Identification of penalizing configurations in computer experiments using screening and metamodel -- Applications in thermal-hydraulics A. M. CEA-DES Bertrand Iooss V. Chabridon 61 17 0 08 Apr 2020
Direct loss minimization algorithms for sparse Gaussian processes Yadi Wei Rishit Sheth Roni Khardon 74 14 0 07 Apr 2020
How Good are Low-Rank Approximations in Gaussian Process Regression? C. Daskalakis P. Dellaportas A. Panos 70 3 0 03 Apr 2020
Energy-Based Processes for Exchangeable Data Mengjiao Yang Bo Dai H. Dai Dale Schuurmans 83 12 0 17 Mar 2020
Linear-time inference for Gaussian Processes on one dimension Jackson Loper David M. Blei John P. Cunningham Liam Paninski 95 17 0 11 Mar 2020
Scalable Uncertainty for Computer Vision with Functional Variational Inference Eduardo D C Carvalho R. Clark Andrea Nicastro Paul H. J. Kelly BDL UQCV 424 22 0 06 Mar 2020
Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations Simone Rossi Markus Heinonen Edwin V. Bonilla Zheyan Shen Maurizio Filippone UQCV BDL 55 0 0 06 Mar 2020
Localising Faster: Efficient and precise lidar-based robot localisation in large-scale environments Li Sun Daniel Adolfsson Martin Magnusson Henrik Andreasson Ingmar Posner T. Duckett 89 30 0 04 Mar 2020
Gaussian Process Policy Optimization Anand Srinivasa Rao Bidipta Sarkar Tejas Narayanan GP 33 0 0 02 Mar 2020
A Framework for Interdomain and Multioutput Gaussian Processes Mark van der Wilk Vincent Dutordoir S. T. John A. Artemev Vincent Adam J. Hensman 109 95 0 02 Mar 2020
Online Binary Space Partitioning Forests Xuhui Fan Bin Li Scott A. Sisson 43 8 0 29 Feb 2020
Efficiently Sampling Functions from Gaussian Process Posteriors James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 85 165 0 21 Feb 2020
Deep Sigma Point Processes M. Jankowiak Geoff Pleiss Jacob R. Gardner BDL 69 23 0 21 Feb 2020
Weakly-supervised Multi-output Regression via Correlated Gaussian Processes Seokhyun Chung Raed Al Kontar Zhenke Wu 39 5 0 19 Feb 2020
Deep Gaussian Markov Random Fields Per Sidén Fredrik Lindsten BDL 61 22 0 18 Feb 2020
Estimating Uncertainty Intervals from Collaborating Networks Tianhui Zhou Yitong Li Yuan Wu David Carlson UQCV 177 17 0 12 Feb 2020
Graph Convolutional Gaussian Processes For Link Prediction Felix L. Opolka Pietro Lio GNN 81 15 0 11 Feb 2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights Theofanis Karaletsos T. Bui BDL 107 24 0 10 Feb 2020
Estimating Latent Demand of Shared Mobility through Censored Gaussian Processes Daniele Gammelli Inon Peled Filipe Rodrigues Dario Pacino H. A. Kurtaran Francisco Câmara Pereira 92 50 0 21 Jan 2020
Scalable Hyperparameter Optimization with Lazy Gaussian Processes Raju Ram Sabine Müller Franz-Josef Pfreundt N. Gauger J. Keuper GP 23 5 0 16 Jan 2020
Doubly Sparse Variational Gaussian Processes Vincent Adam Stefanos Eleftheriadis N. Durrande A. Artemev J. Hensman 85 26 0 15 Jan 2020
Bayesian Quantile and Expectile Optimisation Victor Picheny Henry B. Moss Léonard Torossian N. Durrande 64 21 0 12 Jan 2020
Bayesian task embedding for few-shot Bayesian optimization Steven Atkinson Sayan Ghosh Natarajan Chennimalai-Kumar Genghis Khan Liping Wang BDL 26 1 0 02 Jan 2020
Scalable Gaussian Process Regression for Kernels with a Non-Stationary Phase J. Grasshoff Alexandra Jankowski P. Rostalski 55 3 0 25 Dec 2019
Gaussian Process Latent Variable Model Factorization for Context-aware Recommender Systems Wei Huang R. Xu BDL LRM 22 4 0 19 Dec 2019
Gaussian Process Priors for View-Aware Inference Wenshuai Zhao Ari Heljakka Arno Solin BDL 35 1 0 06 Dec 2019
Ordinal Bayesian Optimisation Victor Picheny Sattar Vakili A. Artemev 55 8 0 05 Dec 2019
Scalable Bayesian Preference Learning for Crowds Edwin Simpson Iryna Gurevych BDL 120 24 0 04 Dec 2019
A Fully Natural Gradient Scheme for Improving Inference of the Heterogeneous Multi-Output Gaussian Process Model Juan J. Giraldo Mauricio A. Alvarez BDL 119 5 0 22 Nov 2019
GP-ALPS: Automatic Latent Process Selection for Multi-Output Gaussian Process Models P. Berkovich E. Perim W. Bruinsma 13 0 0 05 Nov 2019
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO Pablo Morales-Álvarez Pablo Ruiz S. Coughlin Rafael Molina Aggelos K. Katsaggelos 48 14 0 05 Nov 2019
Continual Multi-task Gaussian Processes P. Moreno-Muñoz A. Artés-Rodríguez Mauricio A. Alvarez 80 13 0 31 Oct 2019
Implicit Posterior Variational Inference for Deep Gaussian Processes Haibin Yu Yizhou Chen Zhongxiang Dai K. H. Low Patrick Jaillet 88 43 0 26 Oct 2019
Parametric Gaussian Process Regressors M. Jankowiak Geoffrey Pleiss Jacob R. Gardner UQCV 65 5 0 16 Oct 2019
The Renyi Gaussian Process: Towards Improved Generalization Xubo Yue Raed Al Kontar 140 3 0 15 Oct 2019
Regularized Sparse Gaussian Processes Rui Meng Herbert Lee Braden C. Soper Priyadip Ray 19 0 0 13 Oct 2019
Compositional uncertainty in deep Gaussian processes Ivan Ustyuzhaninov Ieva Kazlauskaite Markus Kaiser Erik Bodin Neill D. F. Campbell Carl Henrik Ek UQCV 95 23 0 17 Sep 2019
Efficient Transfer Bayesian Optimization with Auxiliary Information Tomoharu Iwata Takuma Otsuka 71 2 0 17 Sep 2019