Kijung Yoon

According to our database, Kijung Yoon authored at least 12 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Self-Supervised Discovery of Neural Circuits in Spatially Patterned Neural Responses with Graph Neural Networks.

Kijung Yoon

CoRR, September, 2025

2024

Osteoporosis Prediction from Hand X-ray Images Using Segmentation-for-Classification and Self-Supervised Learning.

Ung Hwang, Chang-Hun Lee, Kijung Yoon

CoRR, 2024

2023

Towards Better Generalization with Flexible Representation of Multi-Module Graph Neural Networks.

Hyungeun Lee, Kijung Yoon

Trans. Mach. Learn. Res., 2023

Hierarchical Joint Graph Learning and Multivariate Time Series Forecasting.

Juhyeon Kim, Hyungeun Lee, Seungwon Yu, Ung Hwang, Wooyul Jung, Miseon Park, Kijung Yoon

CoRR, 2023

Osteoporosis Prediction from Hand and Wrist X-rays using Image Segmentation and Self-Supervised Learning.

Hyungeun Lee, Ung Hwang, Seungwon Yu, Chang-Hun Lee, Kijung Yoon

CoRR, 2023

Hierarchical Joint Graph Learning and Multivariate Time Series Forecasting.

Juhyeon Kim, Hyungeun Lee, Seungwon Yu, Ung Hwang, Wooyeol Jung, KiJung Yoon

IEEE Access, 2023

2022

Towards Better Generalization with Flexible Representation of Multi-Module Graph Neural Networks.

Hyungeun Lee, Hyunmok Park, KiJung Yoon

CoRR, 2022

Two-Argument Activation Functions Learn Soft XOR Operations Like Cortical Neurons.

Juhyeon Kim, A. Emin Orhan, KiJung Yoon, Xaq Pitkow

IEEE Access, 2022

2021

Two-argument activation functions learn soft XOR operations like cortical neurons.

KiJung Yoon, A. Emin Orhan, Juhyun Kim, Xaq Pitkow

CoRR, 2021

Degree Matters: Assessing the Generalization of Graph Neural Network.

Hyunmok Park, KiJung Yoon

Proceedings of the 7th IEEE International Conference on Network Intelligence and Digital Content, 2021

2019

Inference in Probabilistic Graphical Models by Graph Neural Networks.

KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

Reviving and Improving Recurrent Back-Propagation.

Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard S. Zemel

Proceedings of the 35th International Conference on Machine Learning, 2018