63 citations · 148 across the 22 of their papers we have counts for
7 papers · 1 filter
Lifelong Generative Modelling Using Dynamic Expansion Graph Model
Fei Ye, Adrian G. Bors
Variational Autoencoders (VAEs) suffer from degenerated performance, when learning several successive tasks. This is caused by catastrophic forgetting. In order to address the know…
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…
Lifelong Twin Generative Adversarial Networks
Fei Ye, Adrian G. Bors
In this paper, we propose a new continuously learning generative model, called the Lifelong Twin Generative Adversarial Networks (LT-GANs). LT-GANs learns a sequence of tasks from…
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…