Gaussian Process Prior Variational Autoencoders

28 October 2018

Papers citing "Gaussian Process Prior Variational Autoencoders"

33 / 33 papers shown

Title
Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling Xinxing Shi Xiaoyu Jiang Mauricio A. Álvarez BDL 70 0 0 22 May 2025
Compression, Regularity, Randomness and Emergent Structure: Rethinking Physical Complexity in the Data-Driven Era Nima Dehghani AI4CE 61 0 0 12 May 2025
Likelihood-Free Variational Autoencoders Chen Xu Qiang Wang Lijun Sun DiffM DRL 111 0 0 24 Apr 2025
Boundary-enhanced time series data imputation with long-term dependency diffusion models Chunjing Xiao Xue Jiang Xianghe Du Wei Yang Wei Lu Xinyu Wang Kevin Chetty 91 2 0 11 Jan 2025
Latent Space Energy-based Neural ODEs Sheng Cheng Deqian Kong Jianwen Xie Kookjin Lee Ying Nian Wu Yezhou Yang DiffM 341 1 0 05 Sep 2024
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 151 30,069 0 01 Mar 2022
Predictive Modeling of Anatomy with Genetic and Clinical Data Adrian Dalca R. Sridharan M. Sabuncu Polina Golland MedIm 21 7 0 09 Oct 2020
Multimodal Generative Models for Scalable Weakly-Supervised Learning Mike Wu Noah D. Goodman DRL 61 379 0 14 Feb 2018
Learning Disentangled Representations with Semi-Supervised Deep Generative Models Siddharth Narayanaswamy Brooks Paige Jan-Willem van de Meent Alban Desmaison Noah D. Goodman Pushmeet Kohli Frank Wood Philip Torr DRL CoGe 110 359 0 01 Jun 2017
Generative Models of Visually Grounded Imagination Ramakrishna Vedantam Ian S. Fischer Jonathan Huang Kevin Patrick Murphy 46 138 0 30 May 2017
VAE with a VampPrior Jakub M. Tomczak Max Welling GAN BDL 55 628 0 19 May 2017
Inducing Interpretable Representations with Variational Autoencoders N. Siddharth Brooks Paige Alban Desmaison Jan-Willem van de Meent Frank Wood Noah D. Goodman Pushmeet Kohli Philip Torr BDL DRL 43 6 0 22 Nov 2016
Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering Zhuxi Jiang Yin Zheng Huachun Tan Bangsheng Tang Hanning Zhou BDL DRL 62 726 0 16 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 111 674 0 08 Nov 2016
Joint Multimodal Learning with Deep Generative Models Masahiro Suzuki Kotaro Nakayama Y. Matsuo DRL GAN 56 222 0 07 Nov 2016
Deep Variational Canonical Correlation Analysis Weiran Wang Xinchen Yan Honglak Lee Karen Livescu DRL BDL 39 143 0 11 Oct 2016
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 83 1,805 0 15 Jun 2016
Understanding Probabilistic Sparse Gaussian Process Approximations Matthias Bauer Mark van der Wilk C. Rasmussen 41 257 0 15 Jun 2016
Composing graphical models with neural networks for structured representations and fast inference Matthew J. Johnson David Duvenaud Alexander B. Wiltschko S. R. Datta Ryan P. Adams BDL OCL 67 483 0 20 Mar 2016
Auxiliary Deep Generative Models Lars Maaløe C. Sønderby Søren Kaae Sønderby Ole Winther DRL GAN 63 450 0 17 Feb 2016
The Variational Gaussian Process Dustin Tran Rajesh Ranganath David M. Blei BDL 62 184 0 20 Nov 2015
Hierarchical Variational Models Rajesh Ranganath Dustin Tran David M. Blei DRL VLM 60 334 0 07 Nov 2015
Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 189 882 0 06 Nov 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 258 4,143 0 21 May 2015
Deep Convolutional Inverse Graphics Network Tejas D. Kulkarni William F. Whitney Pushmeet Kohli J. Tenenbaum DRL BDL 78 929 0 11 Mar 2015
Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) A. Wilson H. Nickisch GP 59 512 0 03 Mar 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 857 149,474 0 22 Dec 2014
Semi-Supervised Learning with Deep Generative Models Diederik P. Kingma Danilo Jimenez Rezende S. Mohamed Max Welling GAN SSL BDL 68 2,731 0 20 Jun 2014
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models Y. Gal Mark van der Wilk C. Rasmussen 60 150 0 06 Feb 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 367 16,962 0 20 Dec 2013
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 83 1,226 0 26 Sep 2013
Gaussian Process Kernels for Pattern Discovery and Extrapolation A. Wilson Ryan P. Adams GP 56 604 0 18 Feb 2013
Additive Covariance Kernels for High-Dimensional Gaussian Process Modeling N. Durrande D. Ginsbourger O. Roustant L. Carraro 68 100 0 27 Nov 2011