Deep Gaussian Processes

2 November 2012

Papers citing "Deep Gaussian Processes"

42 / 192 papers shown

Title
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
Variational Implicit Processes Chao Ma Yingzhen Li José Miguel Hernández-Lobato BDL 24 68 0 06 Jun 2018
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation Manuel Haussmann Fred Hamprecht M. Kandemir BDL 26 6 0 19 May 2018
Gaussian Process Behaviour in Wide Deep Neural Networks A. G. Matthews Mark Rowland Jiri Hron Richard Turner Zoubin Ghahramani BDL 35 548 0 30 Apr 2018
Posterior Inference for Sparse Hierarchical Non-stationary Models K. Monterrubio-Gómez L. Roininen S. Wade Theo Damoulas Mark Girolami 27 27 0 04 Apr 2018
Learning non-Gaussian Time Series using the Box-Cox Gaussian Process Gonzalo Rios Felipe A. Tobar GP 13 14 0 19 Mar 2018
Gaussian Processes Over Graphs Arun Venkitaraman S. Chatterjee P. Händel 11 37 0 15 Mar 2018
Deep Learning in Mobile and Wireless Networking: A Survey Chaoyun Zhang P. Patras Hamed Haddadi 45 1,304 0 12 Mar 2018
A trans-disciplinary review of deep learning research for water resources scientists Chaopeng Shen AI4CE 33 682 0 06 Dec 2017
Gaussian Process Regression for Arctic Coastal Erosion Forecasting Matthew Kupilik F. Witmer E. MacLeod Caixia Wang T. Ravens 24 15 0 04 Dec 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 19 1,071 0 01 Nov 2017
Auto-Differentiating Linear Algebra Matthias Seeger A. Hetzel Zhenwen Dai Eric Meissner Neil D. Lawrence 17 38 0 24 Oct 2017
Deep Gaussian Covariance Network K. Cremanns D. Roos BDL 24 20 0 17 Oct 2017
Bayesian Alignments of Warped Multi-Output Gaussian Processes Markus Kaiser Clemens Otte Thomas Runkler Carl Henrik Ek 24 19 0 08 Oct 2017
Variational Grid Setting Network Yu-Neng Chuang Zi-Yu Huang Yen-Lung Tsai GAN 21 1 0 30 Sep 2017
Deep Active Learning for Named Entity Recognition Yanyao Shen Hyokun Yun Zachary Chase Lipton Y. Kronrod Anima Anandkumar HAI 30 454 0 19 Jul 2017
DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self Clément Moulin-Frier Tobias Fischer Maxime Petit G. Pointeau J. Puigbò ... Giorgio Metta T. Prescott Y. Demiris Peter Ford Dominey P. Verschure LM&Ro 29 66 0 12 Jun 2017
Doubly Stochastic Variational Inference for Deep Gaussian Processes Hugh Salimbeni M. Deisenroth BDL GP 34 415 0 24 May 2017
Hierarchic Kernel Recursive Least-Squares Hossein Mohamadipanah Mahdi Heydari Girish Chowdhary 25 0 0 14 Apr 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks Christos Louizos Max Welling BDL 21 454 0 06 Mar 2017
Learning Scalable Deep Kernels with Recurrent Structure Maruan Al-Shedivat A. Wilson Yunus Saatchi Zhiting Hu Eric Xing BDL 13 104 0 27 Oct 2016
Random Feature Expansions for Deep Gaussian Processes Kurt Cutajar Edwin V. Bonilla Pietro Michiardi Maurizio Filippone BDL 14 142 0 14 Oct 2016
How priors of initial hyperparameters affect Gaussian process regression models Zexun Chen Bo Wang 18 86 0 25 May 2016
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks Julien Mairal SSL 34 130 0 20 May 2016
Observational-Interventional Priors for Dose-Response Learning Ricardo M. A. Silva CML 14 32 0 05 May 2016
Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis Andreas C. Damianou Neil D. Lawrence Carl Henrik Ek 16 12 0 17 Apr 2016
Cauchy difference priors for edge-preserving Bayesian inversion with an application to X-ray tomography M. Markkanen L. Roininen Janne M. J. Huttunen Sari Lasanen 44 32 0 19 Mar 2016
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors Christos Louizos Max Welling BDL 33 253 0 15 Mar 2016
Inverse Reinforcement Learning via Deep Gaussian Process Ming Jin Andreas C. Damianou Pieter Abbeel C. Spanos OffRL BDL GP 20 22 0 26 Dec 2015
Recurrent Gaussian Processes C. L. C. Mattos Zhenwen Dai Andreas C. Damianou Jeremy Forth G. Barreto Neil D. Lawrence BDL 32 75 0 20 Nov 2015
On the energy landscape of deep networks Pratik Chaudhari Stefano Soatto ODL 40 27 0 20 Nov 2015
Variational Auto-encoded Deep Gaussian Processes Zhenwen Dai Andreas C. Damianou Javier I. González Neil D. Lawrence BDL 24 131 0 19 Nov 2015
Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 61 872 0 06 Nov 2015
Blitzkriging: Kronecker-structured Stochastic Gaussian Processes T. Nickson Tom Gunter C. Lloyd Michael A. Osborne Stephen J. Roberts 19 21 0 27 Oct 2015
A Bayesian approach to constrained single- and multi-objective optimization Paul Feliot Julien Bect E. Vázquez 19 149 0 02 Oct 2015
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 202 745 0 06 Jun 2015
On Sparse variational methods and the Kullback-Leibler divergence between stochastic processes A. G. Matthews J. Hensman Richard Turner Zoubin Ghahramani 30 189 0 27 Apr 2015
Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency Inputs Y. Gal Richard Turner 21 78 0 09 Mar 2015
Hierarchical Mixture-of-Experts Model for Large-Scale Gaussian Process Regression Jun Wei Ng M. Deisenroth 31 51 0 09 Dec 2014
Variational Inference for Uncertainty on the Inputs of Gaussian Process Models Andreas C. Damianou Michalis K. Titsias Neil D. Lawrence 41 25 0 08 Sep 2014
Surpassing Human-Level Face Verification Performance on LFW with GaussianFace Chaochao Lu Xiaoou Tang CVBM 89 333 0 15 Apr 2014