Addressing posterior collapse by splitting decoders in variational recurrent autoencoders-Reference-Cited by-同舟云学术

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Addressing posterior collapse by splitting decoders in variational recurrent autoencoders

Published:2024-02 Issue: Volume:570 Page:127103
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Sun Jianyong,Song Fan^ORCID,Li Qiaohong

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference93 articles.

1. Photorealistic text-to-image diffusion models with deep language understanding;Saharia,2022

2. Imagen video: High definition video generation with diffusion models;Ho,2022

3. Audiolm: a language modeling approach to audio generation;Borsos,2022

4. D. Rezende, S. Mohamed, Variational Inference with Normalizing Flows, in: International Conference on Machine Learning, 2015, pp. 1530–1538.

5. Generative adversarial nets;Goodfellow,2014

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