6 citations · 6 across the 3 of their papers we have counts for
4 papers
Having Second Thoughts? Let's hear it
Jung H. Lee, Sujith Vijayan
Deep learning models loosely mimic bottom-up signal pathways from low-order sensory areas to high-order cognitive areas. After training, DL models can outperform humans on some dom…
Generalization ability and Vulnerabilities to adversarial perturbations: Two sides of the same coin
Jung Hoon Lee, Sujith Vijayan
Deep neural networks (DNNs), the agents of deep learning (DL), require a massive number of parallel/sequential operations, which makes it difficult to comprehend them and impedes p…
Complementary reinforcement learning towards explainable agents
Jung Hoon Lee
Reinforcement learning (RL) algorithms allow agents to learn skills and strategies to perform complex tasks without detailed instructions or expensive labelled training examples. T…
DynMat, a network that can learn after learning
Jung H. Lee
To survive in the dynamically-evolving world, we accumulate knowledge and improve our skills based on experience. In the process, gaining new knowledge does not disrupt our vigilan…