Variational Inference for Longitudinal Data Using Normalizing Flows

24 March 2023

Papers citing "Variational Inference for Longitudinal Data Using Normalizing Flows"

45 / 45 papers shown

Title
A Geometric Perspective on Variational Autoencoders Clément Chadebec S. Allassonnière DRL 54 23 0 15 Sep 2022
Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case Clément Chadebec Louis J. Vincent S. Allassonnière DRL 48 29 0 16 Jun 2022
Simple Video Generation using Neural ODEs David Kanaa Vikram S. Voleti Samira Ebrahimi Kahou Christopher Pal 44 20 0 07 Sep 2021
Topographic VAEs learn Equivariant Capsules Thomas Anderson Keller Max Welling BDL 64 38 0 03 Sep 2021
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder Clément Chadebec Elina Thibeau-Sutre Ninon Burgos S. Allassonnière 85 66 0 30 Apr 2021
Learning Dynamic Alignment via Meta-filter for Few-shot Learning C. Xu Chen Liu Li Zhang Chengjie Wang Jilin Li Feiyue Huang Xiangyang Xue Yanwei Fu 61 105 0 25 Mar 2021
Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation Sunghyun Park Kangyeol Kim Junsoo Lee Jaegul Choo Joonseok Lee Sookyung Kim Edward Choi 81 55 0 16 Oct 2020
Longitudinal Variational Autoencoder S. Ramchandran Gleb Tikhonov Kalle Kujanpää Miika Koskinen Harri Lähdesmäki DRL CML BDL 52 36 0 17 Jun 2020
Dissecting Neural ODEs Stefano Massaroli Michael Poli Jinkyoo Park Atsushi Yamashita Hajime Asama 78 200 0 19 Feb 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 282 10,591 0 17 Feb 2020
Variational Autoencoders with Riemannian Brownian Motion Priors Dimitris Kalatzis David Eklund Georgios Arvanitidis Søren Hauberg BDL DRL 89 49 0 12 Feb 2020
GP-VAE: Deep Probabilistic Time Series Imputation Vincent Fortuin Dmitry Baranchuk Gunnar Rätsch Stephan Mandt BDL AI4TS 49 247 0 09 Jul 2019
Generating Diverse High-Fidelity Images with VQ-VAE-2 Ali Razavi Aaron van den Oord Oriol Vinyals DRL BDL 110 1,788 0 02 Jun 2019
Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit Belinda Tzen Maxim Raginsky DiffM 136 207 0 23 May 2019
Augmented Neural ODEs Emilien Dupont Arnaud Doucet Yee Whye Teh BDL 115 622 0 02 Apr 2019
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders Emile Mathieu Charline Le Lan Chris J. Maddison Ryota Tomioka Yee Whye Teh BDL DRL 59 175 0 17 Jan 2019
Gaussian Process Prior Variational Autoencoders F. P. Casale Adrian Dalca Luca Saglietti Jennifer Listgarten Nicolò Fusi BDL CML 61 136 0 28 Oct 2018
Explorations in Homeomorphic Variational Auto-Encoding Luca Falorsi P. D. Haan Tim R. Davidson Nicola De Cao Maurice Weiler Patrick Forré Taco S. Cohen BDL DRL 79 117 0 12 Jul 2018
High-Resolution Mammogram Synthesis using Progressive Generative Adversarial Networks Dimitrios Korkinof T. Rijken Michael OÑeill J. Yearsley H. Harvey Ben Glocker MedIm 47 65 0 09 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 293 5,024 0 19 Jun 2018
Hamiltonian Variational Auto-Encoder Anthony L. Caterini Arnaud Doucet Dino Sejdinovic BDL DRL 43 96 0 29 May 2018
BRITS: Bidirectional Recurrent Imputation for Time Series Wei Cao Dong Wang Jian Li Hao Zhou Lei Li Yitan Li AI4TS 49 612 0 27 May 2018
Understanding disentangling in $β$ -VAE Christopher P. Burgess I. Higgins Arka Pal Loic Matthey Nicholas Watters Guillaume Desjardins Alexander Lerchner CoGe DRL 52 828 0 10 Apr 2018
Hyperspherical Variational Auto-Encoders Tim R. Davidson Luca Falorsi Nicola De Cao Thomas Kipf Jakub M. Tomczak DRL BDL 94 381 0 03 Apr 2018
Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms Alexandre Bône O. Colliot S. Durrleman 31 37 0 27 Mar 2018
Disentangled Sequential Autoencoder Yingzhen Li Stephan Mandt CoGe 71 270 0 08 Mar 2018
Disentangling by Factorising Hyunjik Kim A. Mnih CoGe OOD 54 1,336 0 16 Feb 2018
The Riemannian Geometry of Deep Generative Models Hang Shao Abhishek Kumar P. T. Fletcher DRL 56 182 0 21 Nov 2017
Metrics for Deep Generative Models Nutan Chen Alexej Klushyn Richard Kurle Xueyan Jiang Justin Bayer Patrick van der Smagt SyDa DRL 56 116 0 03 Nov 2017
Latent Space Oddity: on the Curvature of Deep Generative Models Georgios Arvanitidis Lars Kai Hansen Søren Hauberg DRL 93 267 0 31 Oct 2017
Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks Igor Koval Jean-Baptiste Schiratti A. Routier Michael Bacci O. Colliot S. Allassonnière S. Durrleman 23 23 0 25 Sep 2017
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 161 1,343 0 19 May 2017
VAE with a VampPrior Jakub M. Tomczak Max Welling GAN BDL 63 628 0 19 May 2017
Variational Lossy Autoencoder Xi Chen Diederik P. Kingma Tim Salimans Yan Duan Prafulla Dhariwal John Schulman Ilya Sutskever Pieter Abbeel DRL SSL GAN 116 674 0 08 Nov 2016
Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders Nat Dilokthanakul P. Mediano M. Garnelo M. J. Lee Hugh Salimbeni Kai Arulkumaran Murray Shanahan DRL 57 651 0 08 Nov 2016
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 100 1,805 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 222 3,681 0 26 May 2016
A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues Iulian Serban Alessandro Sordoni Ryan J. Lowe Laurent Charlin Joelle Pineau Aaron Courville Yoshua Bengio BDL 129 1,106 0 19 May 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 213 4,748 0 04 Jan 2016
Importance Weighted Autoencoders Yuri Burda Roger C. Grosse Ruslan Salakhutdinov BDL 236 1,240 0 01 Sep 2015
A Recurrent Latent Variable Model for Sequential Data Junyoung Chung Kyle Kastner Laurent Dinh Kratarth Goel Aaron Courville Yoshua Bengio DRL BDL 80 1,250 0 07 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 278 4,143 0 21 May 2015
MADE: Masked Autoencoder for Distribution Estimation M. Germain Karol Gregor Iain Murray Hugo Larochelle OOD SyDa UQCV 136 863 0 12 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.3K 149,474 0 22 Dec 2014
NICE: Non-linear Independent Components Estimation Laurent Dinh David M. Krueger Yoshua Bengio DRL BDL 118 2,251 0 30 Oct 2014