1 citations · 1 across the 5 of their papers we have counts for
5 papers
Unsupervised Point Cloud Completion through Unbalanced Optimal Transport
Taekyung Lee, Jaemoo Choi, Jaewoong Choi +1
Unpaired point cloud completion is crucial for real-world applications, where ground-truth data for complete point clouds are often unavailable. By learning a completion map from u…
Revealing and Utilizing In-group Favoritism for Graph-based Collaborative Filtering
Hoin Jung, Hyunsoo Cho, Myungje Choi +3
When it comes to a personalized item recommendation system, It is essential to extract users' preferences and purchasing patterns. Assuming that users in the real world form a clus…
Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
Wasserstein Gradient Flow (WGF) describes the gradient dynamics of probability density within the Wasserstein space. WGF provides a promising approach for conducting optimization o…
Analyzing and Improving Optimal-Transport-based Adversarial Networks
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
Optimal Transport (OT) problem aims to find a transport plan that bridges two distributions while minimizing a given cost function. OT theory has been widely utilized in generative…
Universal Approximation Property of Fully Convolutional Neural Networks with Zero Padding
Geonho Hwang, Myungjoo Kang
The Convolutional Neural Network (CNN) is one of the most prominent neural network architectures in deep learning. Despite its widespread adoption, our understanding of its univers…