Looking through the past: better knowledge retention for generative replay in continual learning

V Khan, S Cygert, B Twardowski… - Proceedings of the …, 2023 - openaccess.thecvf.com
In this work, we improve the generative replay in a continual learning setting. We notice that
in VAE-based generative replay, the generated features are quite far from the original ones …
被引用次数：5 相关文章

Looking through the past: better knowledge retention for generative replay in continual learning

V Khan, S Cygert, B Twardowski… - 2023 IEEE/CVF …, 2023 - computer.org
In this work, we improve the generative replay in a continual learning setting. We notice that
in VAE-based generative replay, the generated features are quite far from the original ones …

Looking through the past: better knowledge retention for generative replay in continual learning

V Khan, S Cygert, K Deja, T Trzciński… - arXiv e …, 2023 - ui.adsabs.harvard.edu
In this work, we improve the generative replay in a continual learning setting to perform well
on challenging scenarios. Current generative rehearsal methods are usually benchmarked …

Looking through the past: better knowledge retention for generative replay in continual learning

V Khan, S Cygert, K Deja, T TrzciNski… - IEEE …, 2024 - ieeexplore.ieee.org
In this work, we improve the generative replay in a continual learning setting to perform well
on challenging scenarios. Because of the growing complexity of continual learning tasks, it …

Looking through the past: better knowledge retention for generative replay in continual learning

V Khan, S Cygert, K Deja, T Trzciński, B Twardowski - IEEE Access, 2024 - repo.pw.edu.pl
In this work, we improve the generative replay in a continual learning setting to perform well
on challenging scenarios. Because of the growing complexity of continual learning tasks, it …
[PDF] mostwiedzy.pl

[PDF][PDF] Looking through the past: better knowledge retention for generative replay in continual learning

V KHAN, S CYGERT, K DEJA, T TRZCINSKI… - mostwiedzy.pl
In this work, we improve the generative replay in a continual learning setting to perform well
on challenging scenarios. Because of the growing complexity of continual learning tasks, it …

Looking through the past: better knowledge retention for generative replay in continual learning

V Khan, S Cygert, K Deja, T Trzciński… - arXiv preprint arXiv …, 2023 - arxiv.org
In this work, we improve the generative replay in a continual learning setting to perform well
on challenging scenarios. Current generative rehearsal methods are usually benchmarked …

Looking Through the Past: Better Knowledge Retention for Generative Replay in Continual Learning

V Khan, S Cygert, K Deja, T Trzcinski… - IEEE …, 2024 - ui.adsabs.harvard.edu
In this work, we improve the generative replay in a continual learning setting to perform well
on challenging scenarios. Current generative rehearsal methods are usually benchmarked …

Looking through the past: better knowledge retention for generative replay in continual learning

V Khan, S Cygert, B Twardowski… - 2023 IEEE/CVF …, 2023 - ieeexplore.ieee.org
In this work, we improve the generative replay in a continual learning setting. We notice that
in VAE-based generative replay, the generated features are quite far from the original ones …

Looking through the past: better knowledge retention for generative replay in continual learning

V Khan, S Cygert, K Deja, T Trzciński, B Twardowski - IEEE Access, 2024 - mostwiedzy.pl
In this work, we improve the generative replay in a continual learning setting to perform well
on challenging scenarios. Because of the growing complexity of continual learning tasks, it …