Return of the normal distribution: Flexible deep continual learning with variational auto-encoders-Reference-Cited by-同舟云学术

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Return of the normal distribution: Flexible deep continual learning with variational auto-encoders

Published:2022-10 Issue: Volume:154 Page:397-412
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Hong Yongwon^ORCID,Mundt Martin^ORCID,Park Sungho,Uh Yungjung,Byun Hyeran^ORCID

Funder

National Research Foundation of Korea

Ministry of Science, ICT and Future Planning

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference48 articles.

1. Life-long disentangled representation learning with cross-domain latent homologies;Achille,2018

2. Understanding disentangling in beta-VAE;Burgess,2017

3. Dark experience for general continual learning: a strong, simple baseline;Buzzega,2020

4. Lifelong machine learning;Chen;Synthesis Lectures on Artificial Intelligence and Machine Learning,2018

5. Very deep VAEs generalize autoregressive models and can outperform them on images;Child,2021

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