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Stochastic Variational Deep Kernel Learning

1 November 2016

Papers citing "Stochastic Variational Deep Kernel Learning"

45 / 95 papers shown

Title
Infinitely Wide Graph Convolutional Networks: Semi-supervised Learning via Gaussian Processes Jilin Hu Jianbing Shen B. Yang Ling Shao BDL GNN 89 18 0 26 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 90 290 0 24 Feb 2020
Deep Sigma Point Processes M. Jankowiak Geoff Pleiss Jacob R. Gardner BDL 69 22 0 21 Feb 2020
Being Bayesian about Categorical Probability Taejong Joo U. Chung Minji Seo UQCV BDL 92 61 0 19 Feb 2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights Theofanis Karaletsos T. Bui BDL 104 24 0 10 Feb 2020
On the Validity of Bayesian Neural Networks for Uncertainty Estimation John Mitros Brian Mac Namee UQCV BDL 91 30 0 03 Dec 2019
Online tuning and light source control using a physics-informed Gaussian process Adi A. Hanuka J. Duris J. Shtalenkova Dylan Kennedy A. Edelen Daniel Ratner Xiaobiao Huang 49 20 0 04 Nov 2019
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes Greg Yang 154 202 0 28 Oct 2019
Recurrent Attentive Neural Process for Sequential Data Shenghao Qin Jiacheng Zhu Jimmy Qin Wenshuo Wang Ding Zhao BDL AI4TS 81 38 0 17 Oct 2019
On the expected behaviour of noise regularised deep neural networks as Gaussian processes Arnu Pretorius Herman Kamper Steve Kroon 61 9 0 12 Oct 2019
Deep Kernel Learning via Random Fourier Features Jiaxuan Xie Fanghui Liu Kaijie Wang Xiaolin Huang 46 19 0 07 Oct 2019
Efficient Transfer Bayesian Optimization with Auxiliary Information Tomoharu Iwata Takuma Otsuka 64 2 0 17 Sep 2019
A Fine-Grained Spectral Perspective on Neural Networks Greg Yang Hadi Salman 118 113 0 24 Jul 2019
The Functional Neural Process Christos Louizos Xiahan Shi Klamer Schutte Max Welling BDL 75 77 0 19 Jun 2019
Non-Parametric Calibration for Classification Jonathan Wenger Hedvig Kjellström Rudolph Triebel UQCV 114 82 0 12 Jun 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
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation Greg Yang 185 289 0 13 Feb 2019
Learnable Embedding Space for Efficient Neural Architecture Compression Shengcao Cao Xiaofang Wang Kris Kitani 79 43 0 01 Feb 2019
Meta-Learning Mean Functions for Gaussian Processes Vincent Fortuin Heiko Strathmann Gunnar Rätsch BDL FedML MLT 100 29 0 23 Jan 2019
Physics-informed deep generative models Yibo Yang P. Perdikaris AI4CE PINN 87 59 0 09 Dec 2018
A Gaussian Process perspective on Convolutional Neural Networks Anastasia Borovykh 81 19 0 25 Oct 2018
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes Roman Novak Lechao Xiao Jaehoon Lee Yasaman Bahri Greg Yang Jiri Hron Daniel A. Abolafia Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 121 310 0 11 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
When Gaussian Process Meets Big Data: A Review of Scalable GPs Haitao Liu Yew-Soon Ong Xiaobo Shen Jianfei Cai GP 136 697 0 03 Jul 2018
Variational Implicit Processes Chao Ma Yingzhen Li José Miguel Hernández-Lobato BDL 119 70 0 06 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
Calibrating Deep Convolutional Gaussian Processes Gia-Lac Tran Edwin V. Bonilla John P. Cunningham Pietro Michiardi Maurizio Filippone BDL UQCV 70 43 0 26 May 2018
Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance Neal Jean Sang Michael Xie Stefano Ermon BDL SSL 75 76 0 26 May 2018
Gaussian Process Behaviour in Wide Deep Neural Networks A. G. Matthews Mark Rowland Jiri Hron Richard Turner Zoubin Ghahramani BDL 171 561 0 30 Apr 2018
Constant-Time Predictive Distributions for Gaussian Processes Geoff Pleiss Jacob R. Gardner Kilian Q. Weinberger A. Wilson 67 96 0 16 Mar 2018
The Gaussian Process Autoregressive Regression Model (GPAR) James Requeima Will Tebbutt W. Bruinsma Richard Turner 144 41 0 20 Feb 2018
DeepKSPD: Learning Kernel-matrix-based SPD Representation for Fine-grained Image Recognition M. Engin Lei Wang Luping Zhou Xinwang Liu 60 54 0 11 Nov 2017
Scalable Log Determinants for Gaussian Process Kernel Learning Kun Dong David Eriksson H. Nickisch D. Bindel A. Wilson 58 95 0 09 Nov 2017
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 154 1,100 0 01 Nov 2017
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition Pavel Izmailov Alexander Novikov D. Kropotov 87 62 0 19 Oct 2017
Convolutional Gaussian Processes Mark van der Wilk C. Rasmussen J. Hensman BDL 90 132 0 06 Sep 2017
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks John Bradshaw A. G. Matthews Zoubin Ghahramani BDL AAML 117 172 0 08 Jul 2017
Efficient Correlated Topic Modeling with Topic Embedding Junxian He Zhiting Hu Taylor Berg-Kirkpatrick Ying Huang Eric Xing 57 48 0 01 Jul 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 301 5,882 0 14 Jun 2017
Bayesian GAN Yunus Saatci A. Wilson GAN 91 133 0 26 May 2017
The Kernel Mixture Network: A Nonparametric Method for Conditional Density Estimation of Continuous Random Variables L. Ambrogioni Umut Güçlü Marcel van Gerven E. Maris BDL 186 47 0 19 May 2017
Multimodal Word Distributions Ben Athiwaratkun A. Wilson 87 90 0 27 Apr 2017
Learning Scalable Deep Kernels with Recurrent Structure Maruan Al-Shedivat A. Wilson Yunus Saatchi Zhiting Hu Eric Xing BDL 104 105 0 27 Oct 2016
Random Feature Expansions for Deep Gaussian Processes Kurt Cutajar Edwin V. Bonilla Pietro Michiardi Maurizio Filippone BDL 58 144 0 14 Oct 2016