63 citations · 103 across the 7 of their papers we have counts for
9 papers
Lifelong Infinite Mixture Model Based on Knowledge-Driven Dirichlet Process
Fei Ye, Adrian G. Bors
Recent research efforts in lifelong learning propose to grow a mixture of models to adapt to an increasing number of tasks. The proposed methodology shows promising results in over…
InfoVAEGAN : learning joint interpretable representations by information maximization and maximum likelihood
Fei Ye, Adrian G. Bors
Learning disentangled and interpretable representations is an important step towards accomplishing comprehensive data representations on the manifold. In this paper, we propose a n…
Lifelong Mixture of Variational Autoencoders
Fei Ye, Adrian G. Bors
In this paper, we propose an end-to-end lifelong learning mixture of experts. Each expert is implemented by a Variational Autoencoder (VAE). The experts in the mixture system are j…
Lifelong Teacher-Student Network Learning
Fei Ye, Adrian G. Bors
A unique cognitive capability of humans consists in their ability to acquire new knowledge and skills from a sequence of experiences. Meanwhile, artificial intelligence systems are…
Deep Unsupervised Image Anomaly Detection: An Information Theoretic Framework
Fei Ye, Huangjie Zheng, Chaoqin Huang +1
Surrogate task based methods have recently shown great promise for unsupervised image anomaly detection. However, there is no guarantee that the surrogate tasks share the consisten…
ESAD: End-to-end Deep Semi-supervised Anomaly Detection
Chaoqin Huang, Fei Ye, Peisen Zhao +3
This paper explores semi-supervised anomaly detection, a more practical setting for anomaly detection where a small additional set of labeled samples are provided. We propose a new…