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2020 – today
- 2024
[c5]ByeongChang Jeong, Daegyeom Kim, Hyun-Ghang Jeong, Cheol E. Han:
A Deep Learning Model of Amyloid-${\boldsymbol{\beta }}$ Diffusion Simulation. ICEIC 2024: 1-4- 2023
- [j9]Seoyeon Choi, Dong Geun Park
, Min Jung Kim, Seain Bang, Jungchun Kim, Seunghee Jin, Ki Seok Huh, Donghyun Kim, Jérôme Mitard, Cheol E. Han, Jae Woo Lee:
Automatic Prediction of Metal-Oxide-Semiconductor Field-Effect Transistor Threshold Voltage Using Machine Learning Algorithm. Adv. Intell. Syst. 5(1) (2023) - [j8]Seoyeon Choi, Dong Geun Park, Min Jung Kim, Seain Bang, Jungchun Kim, Seunghee Jin, Ki Seok Huh, Donghyun Kim, Jérôme Mitard, Cheol E. Han, Jae Woo Lee:
Automatic Prediction of Metal-Oxide-Semiconductor Field-Effect Transistor Threshold Voltage Using Machine Learning Algorithm. Adv. Intell. Syst. 5(1) (2023) - [c4]Youjin Seo, ByeongChang Jeong, Yeji Yoon, Daegyeom Kim, JuHong Min, Cheol E. Han:
3D Super Resolution for Non-Isotropic Medical Image Through Multi-Input 3D ResUnet. IJCNN 2023: 1-6 - 2020
- [j7]Emmanouil Giannakakis, Cheol E. Han, Bernd Weber, Frances Hutchings, Marcus Kaiser:
Towards simulations of long-term behavior of neural networks: Modeling synaptic plasticity of connections within and between human brain regions. Neurocomputing 416: 38-44 (2020)
2010 – 2019
- 2019
- [c3]Pilsub Lee, Myungwon Choi, Daegyeom Kim, Suji Lee, Hyun-Ghang Jeong, Cheol E. Han:
Deep learning based decomposition of brain networks. ICAIIC 2019: 349-354 - [c2]Myungwon Choi, Pilsub Lee, Daegyeom Kim, Suji Lee, HyunChul Youn, Hyun-Ghang Jeong, Cheol E. Han:
Brain Network Decomposition by Auto Encoder (AE) and Graph Auto Encoder (GAE). ICONIP (1) 2019: 568-579 - 2015
- [j6]Frances Hutchings, Cheol E. Han, Simon S. Keller, Bernd Weber, Peter Neal Taylor, Marcus Kaiser:
Predicting Surgery Targets in Temporal Lobe Epilepsy through Structural Connectome Based Simulations. PLoS Comput. Biol. 11(12) (2015) - 2014
- [c1]Cheol E. Han, Luis R. Peraza, John-Paul Taylor, Marcus Kaiser:
Predicting age across human lifespan based on structural connectivity from diffusion tensor imaging. BioCAS 2014: 137-140 - 2012
- [j5]Yukikazu Hidaka, Cheol E. Han, Steven L. Wolf, Carolee J. Winstein, Nicolas Schweighofer:
Use It and Improve It or Lose It: Interactions between Arm Function and Use in Humans Post-stroke. PLoS Comput. Biol. 8(2) (2012) - 2011
- [j4]Christoph Echtermeyer, Cheol E. Han, Anna Rotarska-Jagiela, Harald Mohr, Peter Uhlhaas, Marcus Kaiser:
Integrating Temporal and Spatial Scales: Human Structural Network Motifs Across Age and Region of Interest Size. Frontiers Neuroinformatics 5: 10 (2011) - 2010
- [j3]Isao T. Tokuda, Cheol E. Han, Kazuyuki Aihara, Mitsuo Kawato, Nicolas Schweighofer:
The role of chaotic resonance in cerebellar learning. Neural Networks 23(7): 836-842 (2010)
2000 – 2009
- 2008
- [j2]Cheol E. Han, Michael A. Arbib, Nicolas Schweighofer:
Stroke Rehabilitation Reaches a Threshold. PLoS Comput. Biol. 4(8) (2008) - 2006
- [j1]Nicolas Schweighofer, K. Shishida, Cheol E. Han, Yasumasa Okamoto, Saori C. Tanaka, Shigeto Yamawaki, Kenji Doya:
Humans Can Adopt Optimal Discounting Strategy under Real-Time Constraints. PLoS Comput. Biol. 2(11) (2006)
Coauthor Index
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