Unsupervised generative variational continual learning
Continual learning aims at learning a sequence of tasks without forgetting any task. There are mainly three categories in this field: replay methods, regularization-based methods, and parameter isolation methods. Recent research in continual learning generally incorporates two of these methods to ob...
Main Author: | Liu, Guimeng |
---|---|
Other Authors: | Ponnuthurai Nagaratnam Suganthan |
Format: | Thesis-Master by Coursework |
Language: | English |
Published: |
Nanyang Technological University
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/164770 |
Similar Items
-
Unsupervised Learning for Generative Scene Editing and
Motion
by: Fang, David S.
Published: (2024) -
Unsupervised bayesian generative methods
by: Li, Shaohua
Published: (2016) -
Structured sparse representations for supervised and unsupervised learning
by: Zeng, Yijie
Published: (2020) -
Noise tagging and perceptually-informed unsupervised clustering
by: Cai, HongLing
Published: (2023) -
Unsupervised multi-texture image segmentation
by: Neena Mittal
Published: (2008)