The Variational Gaussian Process

20 November 2015

Papers citing "The Variational Gaussian Process"

40 / 40 papers shown

Title
Algorithmic Identification of Essential Exogenous Nodes for Causal Sufficiency in Brain Networks Abdolmahdi Bagheri Mahdi Dehshiri Babak N. Araabi Alireza Akhondi-Asl CML 29 1 0 08 Mar 2024
On the Size and Approximation Error of Distilled Sets Alaa Maalouf M. Tukan Noel Loo Ramin Hasani Mathias Lechner Daniela Rus DD 34 4 0 23 May 2023
Variational Laplace Autoencoders Yookoon Park C. Kim Gunhee Kim BDL DRL 26 21 0 30 Nov 2022
Latent Variable Modelling Using Variational Autoencoders: A survey Vasanth Kalingeri CML DRL 26 2 0 20 Jun 2022
Fast Gaussian Process Posterior Mean Prediction via Local Cross Validation and Precomputation Alec M. Dunton Benjamin W. Priest Amanda Muyskens GP 32 3 0 22 May 2022
Incorporating Sum Constraints into Multitask Gaussian Processes Philipp Pilar Carl Jidling Thomas B. Schon Niklas Wahlström TPM 24 3 0 03 Feb 2022
A Sparse Expansion For Deep Gaussian Processes Liang Ding Rui Tuo Shahin Shahrampour 19 6 0 11 Dec 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models Sam Bond-Taylor Adam Leach Yang Long Chris G. Willcocks VLM TPM 41 481 0 08 Mar 2021
Efficient Semi-Implicit Variational Inference Vincent Moens Hang Ren A. Maraval Rasul Tutunov Jun Wang H. Ammar 85 6 0 15 Jan 2021
Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes Mengdi Xu Wenhao Ding Jiacheng Zhu Zuxin Liu Baiming Chen Ding Zhao CLL OffRL 28 34 0 19 Jun 2020
Probabilistic Autoencoder Vanessa Böhm U. Seljak UQCV BDL DRL 24 32 0 09 Jun 2020
On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder Haowen Xu Wenxiao Chen Jinlin Lai Zhihan Li Youjian Zhao Dan Pei DRL BDL 32 14 0 31 May 2019
Resampled Priors for Variational Autoencoders Matthias Bauer A. Mnih BDL DRL 16 110 0 26 Oct 2018
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 90 953 0 05 Jun 2018
Semi-Implicit Variational Inference Mingzhang Yin Mingyuan Zhou BDL 35 121 0 28 May 2018
Sylvester Normalizing Flows for Variational Inference Rianne van den Berg Leonard Hasenclever Jakub M. Tomczak Max Welling BDL DRL 18 249 0 15 Mar 2018
Semi-Amortized Variational Autoencoders Yoon Kim Sam Wiseman Andrew C. Miller David Sontag Alexander M. Rush BDL DRL 33 243 0 07 Feb 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
Continuous-Time Flows for Efficient Inference and Density Estimation Changyou Chen Chunyuan Li Liquan Chen Wenlin Wang Yunchen Pu Lawrence Carin TPM 46 57 0 04 Sep 2017
Causal Effect Inference with Deep Latent-Variable Models Christos Louizos Uri Shalit Joris Mooij David Sontag R. Zemel Max Welling CML BDL 69 728 0 24 May 2017
Frequentist Consistency of Variational Bayes Yixin Wang David M. Blei BDL 28 204 0 09 May 2017
Semi-Supervised Generation with Cluster-aware Generative Models Lars Maaløe Marco Fraccaro Ole Winther 20 28 0 03 Apr 2017
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks L. Mescheder Sebastian Nowozin Andreas Geiger GAN BDL 49 525 0 17 Jan 2017
Deep Probabilistic Programming Dustin Tran Matthew D. Hoffman Rif A. Saurous E. Brevdo Kevin Patrick Murphy David M. Blei BDL 36 193 0 13 Jan 2017
Adversarial Message Passing For Graphical Models Theofanis Karaletsos GAN 27 29 0 15 Dec 2016
Two Methods For Wild Variational Inference Qiang Liu Yihao Feng BDL 32 19 0 30 Nov 2016
On the Quantitative Analysis of Decoder-Based Generative Models Yuhuai Wu Yuri Burda Ruslan Salakhutdinov Roger C. Grosse GAN 22 223 0 14 Nov 2016
Variational Lossy Autoencoder Xi Chen Diederik P. Kingma Tim Salimans Yan Duan Prafulla Dhariwal John Schulman Ilya Sutskever Pieter Abbeel DRL SSL GAN 47 671 0 08 Nov 2016
Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning Dilin Wang Qiang Liu GAN BDL 38 118 0 06 Nov 2016
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms C. A. Naesseth Francisco J. R. Ruiz Scott W. Linderman David M. Blei BDL 25 107 0 18 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
Structured Inference Networks for Nonlinear State Space Models Rahul G. Krishnan Uri Shalit David Sontag BDL 16 452 0 30 Sep 2016
Discrete Variational Autoencoders J. Rolfe BDL DRL 35 254 0 07 Sep 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 19 1,069 0 16 Aug 2016
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 55 1,797 0 15 Jun 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 97 3,647 0 26 May 2016
Overdispersed Black-Box Variational Inference Francisco J. R. Ruiz Michalis K. Titsias David M. Blei 22 47 0 03 Mar 2016
Automatic Differentiation Variational Inference A. Kucukelbir Dustin Tran Rajesh Ranganath Andrew Gelman David M. Blei 38 709 0 02 Mar 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 44 4,710 0 04 Jan 2016
Hierarchical Variational Models Rajesh Ranganath Dustin Tran David M. Blei DRL VLM 23 335 0 07 Nov 2015