Yong-Min Shin

According to our database, Yong-Min Shin authored at least 14 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Real-time prediction of breast cancer sites using deformation-aware graph neural network.

Kyunghyun Lee, Yong-Min Shin, Minwoo Shin, Jihun Kim, Sunghwan Lim, Won-Yong Shin, Kyungho Yoon

Eng. Appl. Artif. Intell., 2026

2025

DeformMLP: Effective Deformation Prediction for Breast Cancer Using Graph Topology-Assisted MLPs.

Yong-Min Shin, Kyunghyun Lee, Sunghwan Lim, Kyungho Yoon, Won-Yong Shin

Proceedings of the Digital Twin for Healthcare - First International Workshop, 2025

Faithful and Accurate Self-Attention Attribution for Message Passing Neural Networks via the Computation Tree Viewpoint.

Yong-Min Shin, Siqing Li, Xin Cao, Won-Yong Shin

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

PAGE: Prototype-Based Model-Level Explanations for Graph Neural Networks.

Yong-Min Shin, Sun-Woo Kim, Won-Yong Shin

IEEE Trans. Pattern Anal. Mach. Intell., October, 2024

Edgeless-GNN: Unsupervised Representation Learning for Edgeless Nodes.

Yong-Min Shin, Cong Tran, Won-Yong Shin, Xin Cao

IEEE Trans. Emerg. Top. Comput., 2024

Unveiling the unseen potential of graph learning through MLPs: Effective graph learners using propagation-embracing MLPs.

Yong-Min Shin, Won-Yong Shin

Knowl. Based Syst., 2024

On the Feasibility of Fidelity^- for Graph Pruning.

Yong-Min Shin, Won-Yong Shin

CoRR, 2024

Revisiting Attention Weights as Interpretations of Message-Passing Neural Networks.

Yong-Min Shin, Siqing Li, Xin Cao, Won-Yong Shin

CoRR, 2024

Turbo-CF: Matrix Decomposition-Free Graph Filtering for Fast Recommendation.

Jin-Duk Park, Yong-Min Shin, Won-Yong Shin

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

2023

Propagate & Distill: Towards Effective Graph Learners Using Propagation-Embracing MLPs.

Yong-Min Shin, Won-Yong Shin

CoRR, 2023

2022

Time-Series Anomaly Detection with Implicit Neural Representation.

Kyeong-Joong Jeong, Yong-Min Shin

CoRR, 2022

Prototype-Based Explanations for Graph Neural Networks (Student Abstract).

Yong-Min Shin, Sun-Woo Kim, Eun-Bi Yoon, Won-Yong Shin

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Edgeless-GNN: Unsupervised Inductive Edgeless Network Embedding.

Yong-Min Shin, Cong Tran, Won-Yong Shin, Xin Cao

CoRR, 2021

2017

A Study on ROS Vulnerabilities and Countermeasure.

Seyeon Jeong, I-Ju Choi, Yeong-Jin Kim, Yong-Min Shin, Jeong-Hun Han, Goo-Hong Jung, Kyoung-Gon Kim

Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, 2017