An Architecture for Deep, Hierarchical Generative Models

8 December 2016

Papers citing "An Architecture for Deep, Hierarchical Generative Models"

28 / 28 papers shown

Learning Hierarchical Features with Joint Latent Space Energy-Based Prior

215

14 Oct 2023

Variational Predictive Routing with Nested Subjective TimescalesInternational Conference on Learning Representations (ICLR), 2021

Alexey Zakharov

Qinghai Guo

Zafeirios Fountas

BDL AI4TS

183

21 Oct 2021

CatVRNN: Generating Category Texts via Multi-task Learning

239

12 Jul 2021

Kanerva++: extending The Kanerva Machine with differentiable, locally block allocated latent memoryInternational Conference on Learning Representations (ICLR), 2021

Jason Ramapuram

Yan Wu

Alexandros Kalousis

306

20 Feb 2021

Learning Deep-Latent Hierarchies by Stacking Wasserstein Autoencoders

247

07 Oct 2020

Decontextualized learning for interpretable hierarchical representations of visual patternsbioRxiv (bioRxiv), 2020

R. I. Etheredge

M. Schartl

Alex Jordan

148

31 Aug 2020

Neural Language Generation: Formulation, Methods, and Evaluation

Cristina Garbacea

Qiaozhu Mei

411

31 Jul 2020

Self-Reflective Variational Autoencoder

Ifigeneia Apostolopoulou

Elan Rosenfeld

A. Dubrawski

OOD BDL DRL

193

10 Jul 2020

MHVAE: a Human-Inspired Deep Hierarchical Generative Model for Multimodal Representation Learning

154

04 Jun 2020

Progressive Learning and Disentanglement of Hierarchical RepresentationsInternational Conference on Learning Representations (ICLR), 2020

215

24 Feb 2020

A Stable Variational Autoencoder for Text ModellingInternational Conference on Natural Language Generation (INLG), 2019

171

13 Nov 2019

Unsupervised Star Galaxy Classification with Cascade Variational Auto-Encoder

120

30 Oct 2019

Semi-Implicit Stochastic Recurrent Neural NetworksIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019

Mingyuan Zhou

191

28 Oct 2019

Generative Hierarchical Models for Parts, Objects, and Scenes

173

21 Oct 2019

STCN: Stochastic Temporal Convolutional Networks

Emre Aksan

Otmar Hilliges

BDL

295

18 Feb 2019

Adaptive Density Estimation for Generative Models

479

04 Jan 2019

Recent Advances in Autoencoder-Based Representation Learning

Michael Tschannen

Olivier Bachem

Mario Lucic

OOD SSL DRL

284

494

12 Dec 2018

Taming VAEs

Danilo Jimenez Rezende

Fabio Viola

DRL CML

319

193

01 Oct 2018

The challenge of realistic music generation: modelling raw audio at scaleNeural Information Processing Systems (NeurIPS), 2018

Sander Dieleman

Aaron van den Oord

Karen Simonyan

328

190

26 Jun 2018

Associative Compression Networks for Representation Learning

258

06 Apr 2018

Online Learning with Gated Linear Networks

376

05 Dec 2017

Auxiliary Guided Autoregressive Variational Autoencoders

Thomas Lucas

Jakob Verbeek

GAN DRL

177

30 Nov 2017

Z-Forcing: Training Stochastic Recurrent Networks

343

195

15 Nov 2017

Deep Regression Bayesian Network and Its Applications

104

13 Oct 2017

Towards Deeper Understanding of Variational Autoencoding Models

286

163

28 Feb 2017

Learning Hierarchical Features from Generative Models

282

27 Feb 2017

A Hybrid Convolutional Variational Autoencoder for Text GenerationConference on Empirical Methods in Natural Language Processing (EMNLP), 2017

Stanislau Semeniuta

Aliaksei Severyn

Erhardt Barth

289

266

08 Feb 2017

PixelCNN Models with Auxiliary Variables for Natural Image Modeling

Alexander Kolesnikov

Christoph H. Lampert

GAN

262

24 Dec 2016