61 citations · 144 across the 7 of their papers we have counts for
7 papers
Verifying Design through Generative Visualization of Neural Activities
Pan Wang, Danlin Peng, Simiao Yu +4
Current neuroscience focused approaches for evaluating the effectiveness of a design do not use direct visualisation of mental activity. A recurrent neural network is used as the e…
Topology Distance: A Topology-Based Approach For Evaluating Generative Adversarial Networks
Danijela Horak, Simiao Yu, Gholamreza Salimi-Khorshidi
Automatic evaluation of the goodness of Generative Adversarial Networks (GANs) has been a challenge for the field of machine learning. In this work, we propose a distance complemen…
ILCRO: Making Importance Landscapes Flat Again
Vincent Moens, Simiao Yu, Gholamreza Salimi-Khorshidi
Convolutional neural networks have had a great success in numerous tasks, including image classification, object detection, sequence modelling, and many more. It is generally assum…
Generative Creativity: Adversarial Learning for Bionic Design
Simiao Yu, Hao Dong, Pan Wang +2
Bionic design refers to an approach of generative creativity in which a target object (e.g. a floor lamp) is designed to contain features of biological source objects (e.g. flowers…
TensorLayer: A Versatile Library for Efficient Deep Learning Development
Hao Dong, Akara Supratak, Luo Mai +4
Deep learning has enabled major advances in the fields of computer vision, natural language processing, and multimedia among many others. Developing a deep learning system is arduo…
Semantic Image Synthesis via Adversarial Learning
Hao Dong, Simiao Yu, Chao Wu +1
In this paper, we propose a way of synthesizing realistic images directly with natural language description, which has many useful applications, e.g. intelligent image manipulation…