A Plug-in Method for Representation Factorization in Connectionist Models

• Published in: IEEE transaction on neural networks and learning systems Vol. 33; no. 8; pp. 3792 - 3803
• Main Authors: Yoon, Jee Seok, Roh, Myung-Cheol, Suk, Heung-Il
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.08.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Ablation; Computer vision; Correlation; Decomposition; Factorization; few-shot learning; Gallium nitride; Generative adversarial networks; image-to-image translation; Information theory; Learning systems; Mutual information; Neural networks; Plugs; representation learning; Representations; Semantics; style transfer; Task analysis

In this article, we focus on decomposing latent representations in generative adversarial networks or learned feature representations in deep autoencoders into semantically controllable factors in a semisupervised manner, without modifying the original trained models. Particularly, we propose factor...