Scalable Variational Gaussian Process Classification

7 November 2014

Papers citing "Scalable Variational Gaussian Process Classification"

50 / 337 papers shown

Title
Non-Parametric Calibration for Classification Jonathan Wenger Hedvig Kjellström Rudolph Triebel UQCV 114 82 0 12 Jun 2019
Kernelized Capsule Networks Taylor W. Killian Justin A. Goodwin Olivia M. Brown Sung-Hyun Son GAN 52 2 0 07 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 197 1,707 0 06 Jun 2019
Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel Xin Qiu Elliot Meyerson Risto Miikkulainen UQCV 84 54 0 03 Jun 2019
Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over Simplex Yufei Cui Wuguannan Yao Qiao Li Antoni B. Chan Chun Jason Xue 34 4 0 29 May 2019
Adversarial Robustness Guarantees for Classification with Gaussian Processes Arno Blaas A. Patané Luca Laurenti L. Cardelli Marta Z. Kwiatkowska Stephen J. Roberts GP AAML 75 21 0 28 May 2019
Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation Théo Galy-Fajou F. Wenzel Christian Donner Manfred Opper 60 30 0 23 May 2019
Efficient Deep Gaussian Process Models for Variable-Sized Input I. Laradji Mark Schmidt Vladimir Pavlovic Minyoung Kim GP BDL 33 3 0 16 May 2019
Distribution Calibration for Regression Hao Song Tom Diethe Meelis Kull Peter A. Flach UQCV 192 112 0 15 May 2019
Graph Convolutional Gaussian Processes Ian Walker Ben Glocker GNN 118 36 0 14 May 2019
Multi-fidelity classification using Gaussian processes: accelerating the prediction of large-scale computational models F. Sahli Costabal P. Perdikaris E. Kuhl D. Hurtado AI4CE 43 48 0 09 May 2019
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features Arno Solin Manon Kok 66 23 0 10 Apr 2019
Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources Edwin Simpson S. Reece Stephen J. Roberts 64 3 0 05 Apr 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 62 230 0 19 Mar 2019
Functional Variational Bayesian Neural Networks Shengyang Sun Guodong Zhang Jiaxin Shi Roger C. Grosse BDL 65 241 0 14 Mar 2019
Scalable Grouped Gaussian Processes via Direct Cholesky Functional Representations A. Dahl Edwin V. Bonilla 16 0 0 10 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
Local Function Complexity for Active Learning via Mixture of Gaussian Processes Danny Panknin Stefan Chmiela Klaus-Robert Muller Shinichi Nakajima 73 0 0 27 Feb 2019
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era N. Durrande Vincent Adam L. Bordeaux Stefanos Eleftheriadis J. Hensman 68 26 0 26 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
Functional Regularisation for Continual Learning with Gaussian Processes Michalis K. Titsias Jonathan Richard Schwarz A. G. Matthews Razvan Pascanu Yee Whye Teh CLL BDL 71 187 0 31 Jan 2019
Variational bridge constructs for approximate Gaussian process regression W. Ward Mauricio A. Alvarez 13 1 0 07 Jan 2019
Scalable GAM using sparse variational Gaussian processes Vincent Adam N. Durrande S. T. John 33 2 0 28 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
Neural Non-Stationary Spectral Kernel Sami Remes Markus Heinonen Samuel Kaski BDL 50 9 0 27 Nov 2018
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds David Reeb Andreas Doerr S. Gerwinn Barbara Rakitsch GP 71 34 0 29 Oct 2018
Learning and Interpreting Multi-Multi-Instance Learning Networks Alessandro Tibo M. Jaeger P. Frasconi AI4CE 138 23 0 26 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 19 0 0 16 Oct 2018
Harmonizable mixture kernels with variational Fourier features Zheyan Shen Markus Heinonen Samuel Kaski 81 17 0 10 Oct 2018
Deep learning with differential Gaussian process flows Pashupati Hegde Markus Heinonen Harri Lähdesmäki Samuel Kaski BDL 85 42 0 09 Oct 2018
Deep convolutional Gaussian processes Kenneth Blomqvist Samuel Kaski Markus Heinonen BDL 86 61 0 06 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 149 1,105 0 28 Sep 2018
Gaussian process classification using posterior linearisation Á. F. García-Fernández Filip Tronarp Simo Särkkä 62 11 0 13 Sep 2018
Non-Parametric Variational Inference with Graph Convolutional Networks for Gaussian Processes Linfeng Liu Liping Liu BDL 25 0 0 08 Sep 2018
Learning Invariances using the Marginal Likelihood Mark van der Wilk Matthias Bauer S. T. John J. Hensman 92 86 0 16 Aug 2018
Fully Scalable Gaussian Processes using Subspace Inducing Inputs A. Panos P. Dellaportas Michalis K. Titsias 49 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 133 697 0 03 Jul 2018
Spatiotemporal Prediction of Ambulance Demand using Gaussian Process Regression Seth Nabarro Tristan Fletcher John Shawe-Taylor GP 11 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 76 15 0 26 Jun 2018
Scalable Multi-Class Bayesian Support Vector Machines for Structured and Unstructured Data Martin Wistuba Ambrish Rawat BDL 52 2 0 07 Jun 2018
Grouped Gaussian Processes for Solar Power Prediction A. Dahl Edwin V. Bonilla 15 20 0 07 Jun 2018
Finding Convincing Arguments Using Scalable Bayesian Preference Learning Edwin Simpson Iryna Gurevych BDL 64 52 0 06 Jun 2018
Deep Gaussian Processes with Convolutional Kernels Vinayak Kumar Vaibhav Singh P. K. Srijith Andreas C. Damianou BDL GP 99 30 0 05 Jun 2018
Deep Mixed Effect Model using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare Ingyo Chung Saehoon Kim Juho Lee Kwang Joon Kim Sung Ju Hwang Eunho Yang BDL FedML 82 16 0 05 Jun 2018
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification Dimitrios Milios Raffaello Camoriano Pietro Michiardi Lorenzo Rosasco Maurizio Filippone UQCV 78 75 0 28 May 2018
Efficient Inference in Multi-task Cox Process Models Virginia Aglietti Theodoros Damoulas Edwin V. Bonilla 60 8 0 24 May 2018
Variational Learning on Aggregate Outputs with Gaussian Processes H. Law Dino Sejdinovic E. Cameron T. Lucas Seth Flaxman K. Battle Kenji Fukumizu 48 38 0 22 May 2018
Heterogeneous Multi-output Gaussian Process Prediction P. Moreno-Muñoz Antonio Artés-Rodríguez Mauricio A. Alvarez 59 72 0 19 May 2018
Scalable Generalized Dynamic Topic Models P. Jähnichen F. Wenzel Marius Kloft Stephan Mandt BDL 88 40 0 21 Mar 2018