Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling

22 May 2025

Papers citing "Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling"

26 / 26 papers shown

Title
Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression Robert Allison Anthony Stephenson F. Samuel Edward O. Pyzer-Knapp UQCV 44 4 0 26 Jun 2023
Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes Ba-Hien Tran Babak Shahbaba Stephan Mandt Maurizio Filippone SyDa BDL UQCV 46 6 0 09 Feb 2023
Variational sparse inverse Cholesky approximation for latent Gaussian processes via double Kullback-Leibler minimization JIAN-PENG Cao Myeongjong Kang Felix Jimenez H. Sang Florian Schäfer Matthias Katzfuss 50 7 0 30 Jan 2023
Markovian Gaussian Process Variational Autoencoders Harrison Zhu Carles Balsells Rodas Yingzhen Li BDL AI4TS 58 16 0 12 Jul 2022
Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference Myeong K. Kang Matthias Katzfuss 41 24 0 29 Dec 2021
Spatio-Temporal Variational Gaussian Processes Oliver Hamelijnck William J. Wilkinson Niki A. Loppi Arno Solin Theodoros Damoulas AI4TS 35 34 0 02 Nov 2021
Sparse within Sparse Gaussian Processes using Neighbor Information Gia-Lac Tran Dimitrios Milios Pietro Michiardi Maurizio Filippone 11 16 0 10 Nov 2020
Scalable Gaussian Process Variational Autoencoders Metod Jazbec Matthew Ashman Vincent Fortuin Michael Pearce Stephan Mandt Gunnar Rätsch DRL BDL 43 27 0 26 Oct 2020
Sparse Gaussian Process Variational Autoencoders Matthew Ashman Jonathan So Will Tebbutt Vincent Fortuin Michael Pearce Richard Turner 71 35 0 20 Oct 2020
Fast Variational Learning in State-Space Gaussian Process Models Paul E. Chang William J. Wilkinson Mohammad Emtiyaz Khan Arno Solin BDL 21 24 0 09 Jul 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 182 10,591 0 17 Feb 2020
Doubly Sparse Variational Gaussian Processes Vincent Adam Stefanos Eleftheriadis N. Durrande A. Artemev J. Hensman 35 25 0 15 Jan 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 218 42,038 0 03 Dec 2019
GP-VAE: Deep Probabilistic Time Series Imputation Vincent Fortuin Dmitry Baranchuk Gunnar Rätsch Stephan Mandt BDL AI4TS 46 247 0 09 Jul 2019
Generating Diverse High-Fidelity Images with VQ-VAE-2 Ali Razavi Aaron van den Oord Oriol Vinyals DRL BDL 103 1,788 0 02 Jun 2019
Gaussian Process Prior Variational Autoencoders F. P. Casale Adrian Dalca Luca Saglietti Jennifer Listgarten Nicolò Fusi BDL CML 40 135 0 28 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 61 1,088 0 28 Sep 2018
Handling Incomplete Heterogeneous Data using VAEs A. Nazábal Pablo Martínez Olmos Zoubin Ghahramani Isabel Valera 37 345 0 10 Jul 2018
Disentangling by Factorising Hyunjik Kim A. Mnih CoGe OOD 42 1,336 0 16 Feb 2018
A general framework for Vecchia approximations of Gaussian processes Matthias Katzfuss J. Guinness 29 249 0 21 Aug 2017
Billion-scale similarity search with GPUs Jeff Johnson Matthijs Douze Hervé Jégou 157 3,682 0 28 Feb 2017
Ladder Variational Autoencoders C. Sønderby T. Raiko Lars Maaløe Søren Kaae Sønderby Ole Winther BDL DRL 70 907 0 06 Feb 2016
Deep Kalman Filters Rahul G. Krishnan Uri Shalit David Sontag BDL AI4TS 49 372 0 16 Nov 2015
MCMC for Variationally Sparse Gaussian Processes J. Hensman A. G. Matthews Maurizio Filippone Zoubin Ghahramani 40 141 0 12 Jun 2015
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 69 902 0 17 Feb 2014
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 77 1,226 0 26 Sep 2013