Kijung Yoon

Orcid: 0000-0001-5574-3299

According to our database1, Kijung Yoon authored at least 14 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
A Comparative Study of Adaptation Strategies for Time Series Foundation Models in Anomaly Detection.
CoRR, January, 2026

2025
A Multimodal Approach to Alzheimer's Diagnosis: Geometric Insights from Cube Copying and Cognitive Assessments.
CoRR, December, 2025

Self-Supervised Discovery of Neural Circuits in Spatially Patterned Neural Responses with Graph Neural Networks.
CoRR, September, 2025

2024
Osteoporosis Prediction from Hand X-ray Images Using Segmentation-for-Classification and Self-Supervised Learning.
CoRR, 2024

2023
Towards Better Generalization with Flexible Representation of Multi-Module Graph Neural Networks.
Trans. Mach. Learn. Res., 2023

Hierarchical Joint Graph Learning and Multivariate Time Series Forecasting.
CoRR, 2023

Osteoporosis Prediction from Hand and Wrist X-rays using Image Segmentation and Self-Supervised Learning.
CoRR, 2023

Hierarchical Joint Graph Learning and Multivariate Time Series Forecasting.
IEEE Access, 2023

2022
Towards Better Generalization with Flexible Representation of Multi-Module Graph Neural Networks.
CoRR, 2022

Two-Argument Activation Functions Learn Soft XOR Operations Like Cortical Neurons.
IEEE Access, 2022

2021
Two-argument activation functions learn soft XOR operations like cortical neurons.
CoRR, 2021

Degree Matters: Assessing the Generalization of Graph Neural Network.
Proceedings of the 7th IEEE International Conference on Network Intelligence and Digital Content, 2021

2019
Inference in Probabilistic Graphical Models by Graph Neural Networks.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
Reviving and Improving Recurrent Back-Propagation.
Proceedings of the 35th International Conference on Machine Learning, 2018


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