41 citations · 203 across the 38 of their papers we have counts for
6 papers · 1 filter
An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks
Giyoung Jeon, Haedong Jeong, Jaesik Choi
Deep generative neural networks (DGNNs) have achieved realistic and high-quality data generation. In particular, the adversarial training scheme has been applied to many DGNNs and…
IDEALEM: Statistical Similarity Based Data Reduction
Dongeun Lee, Alex Sim, Jaesik Choi +1
Many applications such as scientific simulation, sensing, and power grid monitoring tend to generate massive amounts of data, which should be compressed first prior to storage and…
Why Do Masked Neural Language Models Still Need Common Sense Knowledge?
Sunjae Kwon, Cheongwoong Kang, Jiyeon Han +1
Currently, contextualized word representations are learned by intricate neural network models, such as masked neural language models (MNLMs). The new representations significantly…
A Single Multi-Task Deep Neural Network with Post-Processing for Object Detection with Reasoning and Robotic Grasp Detection
Dongwon Park, Yonghyeok Seo, Dongju Shin +2
Recently, robotic grasp detection (GD) and object detection (OD) with reasoning have been investigated using deep neural networks (DNNs). There have been works to combine these mul…
Confirmatory Bayesian Online Change Point Detection in the Covariance Structure of Gaussian Processes
Jiyeon Han, Kyowoon Lee, Anh Tong +1
In the analysis of sequential data, the detection of abrupt changes is important in predicting future changes. In this paper, we propose statistical hypothesis tests for detecting…
Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks
Woo-Jeoung Nam, Shir Gur, Jaesik Choi +2
As Deep Neural Networks (DNNs) have demonstrated superhuman performance in a variety of fields, there is an increasing interest in understanding the complex internal mechanisms of…