7 citations · 11 across the 9 of their papers we have counts for
4 papers · 1 filter
Variational Autoencoder Learns Better Feature Representations for EEG-based Obesity Classification
Yuan Yue, Jeremiah D. Deng, Dirk De Ridder +2
Obesity is a common issue in modern societies today that can lead to various diseases and significantly reduced quality of life. Currently, research has been conducted to investiga…
Finding neural signatures for obesity through feature selection on source-localized EEG
Yuan Yue, Dirk De Ridder, Patrick Manning +2
Obesity is a serious issue in the modern society and is often associated to significantly reduced quality of life. Current research conducted to explore obesity-related neurologica…
Variational Transfer Learning using Cross-Domain Latent Modulation
Jinyong Hou, Jeremiah D. Deng, Stephen Cranefield +1
To successfully apply trained neural network models to new domains, powerful transfer learning solutions are essential. We propose to introduce a novel cross-domain latent modulati…
Cross-Domain Latent Modulation for Variational Transfer Learning
Jinyong Hou, Jeremiah D. Deng, Stephen Cranefield +1
We propose a cross-domain latent modulation mechanism within a variational autoencoders (VAE) framework to enable improved transfer learning. Our key idea is to procure deep repres…