Doubly Stochastic Variational Inference for Deep Gaussian Processes

24 May 2017

Papers citing "Doubly Stochastic Variational Inference for Deep Gaussian Processes"

30 / 230 papers shown

Title
Bayesian Image Classification with Deep Convolutional Gaussian Processes Vincent Dutordoir Mark van der Wilk A. Artemev J. Hensman UQCV BDL 24 32 0 15 Feb 2019
Scalable GAM using sparse variational Gaussian processes Vincent Adam N. Durrande S. T. John 22 2 0 28 Dec 2018
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature Franz J. Király Bilal A. Mateen R. Sonabend 18 10 0 18 Dec 2018
Non-Factorised Variational Inference in Dynamical Systems Alessandro Davide Ialongo Mark van der Wilk J. Hensman C. Rasmussen 19 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 27 121 0 10 Dec 2018
Data Association with Gaussian Processes Markus Kaiser Clemens Otte Thomas Runkler Carl Henrik Ek 17 0 0 16 Oct 2018
Harmonizable mixture kernels with variational Fourier features Zheyan Shen Markus Heinonen Samuel Kaski 33 17 0 10 Oct 2018
Deep learning with differential Gaussian process flows Pashupati Hegde Markus Heinonen Harri Lähdesmäki Samuel Kaski BDL 15 42 0 09 Oct 2018
Deep convolutional Gaussian processes Kenneth Blomqvist Samuel Kaski Markus Heinonen BDL 30 60 0 06 Oct 2018
InfoSSM: Interpretable Unsupervised Learning of Nonparametric State-Space Model for Multi-modal Dynamics Young-Jin Park Han-Lim Choi 9 0 0 19 Sep 2018
Bayesian Semi-supervised Learning with Graph Gaussian Processes Yin Cheng Ng Nicolo Colombo Ricardo M. A. Silva BDL 30 89 0 12 Sep 2018
Efficient Global Optimization using Deep Gaussian Processes Ali Hebbal Loïc Brevault M. Balesdent El-Ghazali Talbi N. Melab 19 19 0 11 Sep 2018
Structured Bayesian Gaussian process latent variable model: applications to data-driven dimensionality reduction and high-dimensional inversion Steven Atkinson N. Zabaras 22 36 0 11 Jul 2018
Conditional Neural Processes M. Garnelo Dan Rosenbaum Chris J. Maddison Tiago Ramalho D. Saxton Murray Shanahan Yee Whye Teh Danilo Jimenez Rezende S. M. Ali Eslami UQCV BDL 22 677 0 04 Jul 2018
When Gaussian Process Meets Big Data: A Review of Scalable GPs Haitao Liu Yew-Soon Ong Xiaobo Shen Jianfei Cai GP 16 681 0 03 Jul 2018
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo Marton Havasi José Miguel Hernández-Lobato J. J. Murillo-Fuentes BDL 19 96 0 14 Jun 2018
Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty Hao Zhou Yunyang Xiong Vikas Singh UQCV BDL 52 4 0 10 Jun 2018
Deep Gaussian Processes with Convolutional Kernels Vinayak Kumar Vaibhav Singh P. K. Srijith Andreas C. Damianou BDL GP 17 29 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 22 16 0 05 Jun 2018
Structured Bayesian Gaussian process latent variable model Steven Atkinson N. Zabaras 6 5 0 22 May 2018
Variational zero-inflated Gaussian processes with sparse kernels Pashupati Hegde Markus Heinonen Samuel Kaski 14 5 0 13 Mar 2018
Probabilistic Recurrent State-Space Models Andreas Doerr Christian Daniel Martin Schiegg D. Nguyen-Tuong S. Schaal Marc Toussaint Sebastian Trimpe 17 121 0 31 Jan 2018
Deep Gaussian Processes with Decoupled Inducing Inputs Marton Havasi José Miguel Hernández-Lobato J. J. Murillo-Fuentes GP UQCV BDL 11 5 0 09 Jan 2018
How Deep Are Deep Gaussian Processes? Matthew M. Dunlop Mark Girolami Andrew M. Stuart A. Teckentrup GP 19 131 0 30 Nov 2017
Gaussian Process Neurons Learn Stochastic Activation Functions Sebastian Urban Marcus Basalla Patrick van der Smagt BDL 41 4 0 29 Nov 2017
Structured Variational Inference for Coupled Gaussian Processes Vincent Adam 17 2 0 03 Nov 2017
Deep Recurrent Gaussian Process with Variational Sparse Spectrum Approximation Roman Föll B. Haasdonk Markus Hanselmann Holger Ulmer BDL 20 6 0 02 Nov 2017
Bayesian Alignments of Warped Multi-Output Gaussian Processes Markus Kaiser Clemens Otte Thomas Runkler Carl Henrik Ek 30 19 0 08 Oct 2017
Generic Inference in Latent Gaussian Process Models Edwin V. Bonilla K. Krauth Amir Dezfouli BDL 23 28 0 02 Sep 2016
Manifold Gaussian Processes for Regression Roberto Calandra Jan Peters C. Rasmussen M. Deisenroth 92 271 0 24 Feb 2014