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Sunghwan Joo
Sunghwan Joo
Verified email at skku.edu
Title
Cited by
Cited by
Year
Fooling neural network interpretations via adversarial model manipulation
J Heo, S Joo, T Moon
Advances in neural information processing systems 32, 2019
2392019
Subtask gated networks for non-intrusive load monitoring
C Shin, S Joo, J Yim, H Lee, T Moon, W Rhee
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 1150-1157, 2019
1262019
Swift: Swin 4d fmri transformer
P Kim, J Kwon, S Joo, S Bae, D Lee, Y Jung, S Yoo, J Cha, T Moon
Advances in Neural Information Processing Systems 36, 42015-42037, 2023
142023
Towards more robust interpretation via local gradient alignment
S Joo, S Jeong, J Heo, A Weller, T Moon
Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8168-8176, 2023
82023
DoPAMINE: Double-sided masked CNN for pixel adaptive multiplicative noise despeckling
S Joo, S Cha, T Moon
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4031-4038, 2019
62019
Debiased Learning via Composed Conceptual Sensitivity Regularization
S Joo, T Moon
IEEE Access, 2024
2024
SwiFT: Swin 4D fMRI Transformer
P Yongho Kim, J Kwon, S Joo, S Bae, D Lee, Y Jung, S Yoo, J Cha, ...
arXiv e-prints, arXiv: 2307.05916, 2023
2023
Supplementary Material for Fooling Neural Network Interpretations via Adversarial Model Manipulation
J Heo, S Joo, T Moon
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Articles 1–8