5 citations · 10 across the 2 of their papers we have counts for
3 papers
cs.SE2022★ 5 cited
DeepRNG: Towards Deep Reinforcement Learning-Assisted Generative Testing of Software
Chuan-Yung Tsai, Graham W. Taylor
Although machine learning (ML) has been successful in automating various software engineering needs, software testing still remains a highly challenging topic. In this paper, we ai…
cs.CV2020
FusedProp: Towards Efficient Training of Generative Adversarial Networks
Zachary Polizzi, Chuan-Yung Tsai
Generative adversarial networks (GANs) are capable of generating strikingly realistic samples but state-of-the-art GANs can be extremely computationally expensive to train. In this…
cs.NE2015★ 5 cited
Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework
Chuan-Yung Tsai, David D. Cox
A central challenge in sensory neuroscience is describing how the activity of populations of neurons can represent useful features of the external environment. However, while neuro…