Information Theoretic Learning-Enhanced Dual-Generative Adversarial Networks With Causal Representation for Robust OOD Generalization

Recently, machine/deep learning techniques are achieving remarkable success in a variety of intelligent control and management systems, promising to change the future of artificial intelligence (AI) scenarios. However, they still suffer from some intractable difficulty or limitations for model train...

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Vydané v:	IEEE transaction on neural networks and learning systems Ročník 36; číslo 2; s. 2066 - 2079
Hlavní autori:	Zhou, Xiaokang, Zheng, Xuzhe, Shu, Tian, Liang, Wei, Wang, Kevin I-Kai, Qi, Lianyong, Shimizu, Shohei, Jin, Qun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.02.2025
Predmet:	Autoencoder (AE) causal representation learning (CRL) Data models deep learning Feature extraction generative adversarial network (GAN) information theoretic learning (ITL) Object oriented modeling out-of-distribution (OOD) Predictive models Representation learning Task analysis Training
ISSN:	2162-237X, 2162-2388, 2162-2388
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