| Controllable generative adversarial network M Lee, J Seok Ieee Access 7, 28158-28169, 2019 | 106 | 2019 |
| A mathematical investigation of hallucination and creativity in GPT models M Lee Mathematics 11 (10), 2320, 2023 | 88 | 2023 |
| Transformer architecture and attention mechanisms in genome data analysis: a comprehensive review SR Choi, M Lee Biology 12 (7), 1033, 2023 | 78 | 2023 |
| Heterogeneous structure omnidirectional strain sensor arrays with cognitively learned neural networks JH Lee, SH Kim, JS Heo, JY Kwak, CW Park, I Kim, M Lee, HH Park, ... Advanced Materials 35 (13), 2208184, 2023 | 67 | 2023 |
| Superstargan: Generative adversarial networks for image-to-image translation in large-scale domains K Ko, T Yeom, M Lee Neural Networks 162, 330-339, 2023 | 55 | 2023 |
| Portfolio management via two-stage deep learning with a joint cost H Yun, M Lee, YS Kang, J Seok Expert Systems with Applications 143, 113041, 2020 | 55 | 2020 |
| Mathematical analysis and performance evaluation of the gelu activation function in deep learning M Lee Journal of Mathematics 2023 (1), 4229924, 2023 | 43 | 2023 |
| Recent advances in deep learning for protein-protein interaction analysis: A comprehensive review M Lee Molecules 28 (13), 5169, 2023 | 37 | 2023 |
| Gelu activation function in deep learning: a comprehensive mathematical analysis and performance M Lee arXiv preprint arXiv:2305.12073, 2023 | 36 | 2023 |
| TextControlGAN: Text-to-image synthesis with controllable generative adversarial networks H Ku, M Lee Applied Sciences 13 (8), 5098, 2023 | 36 | 2023 |
| Recent advances in generative adversarial networks for gene expression data: a comprehensive review M Lee Mathematics 11 (14), 3055, 2023 | 33 | 2023 |
| Regularization methods for generative adversarial networks: An overview of recent studies M Lee, J Seok arXiv preprint arXiv:2005.09165, 2020 | 32 | 2020 |
| Deep learning in CRISPR-Cas systems: a review of recent studies M Lee Frontiers in Bioengineering and Biotechnology 11, 1226182, 2023 | 25 | 2023 |
| Deep learning techniques with genomic data in cancer prognosis: a comprehensive review of the 2021–2023 literature M Lee Biology 12 (7), 893, 2023 | 24 | 2023 |
| A mathematical interpretation of autoregressive generative pre-trained transformer and self-supervised learning M Lee Mathematics 11 (11), 2451, 2023 | 23 | 2023 |
| Stock price prediction through the sentimental analysis of news articles J Kim, J Seo, M Lee, J Seok 2019 Eleventh International Conference on Ubiquitous and Future Networks …, 2019 | 22 | 2019 |
| Score-guided generative adversarial networks M Lee, J Seok Axioms 11 (12), 701, 2022 | 18 | 2022 |
| Inverse design of nanophotonic devices using generative adversarial networks W Kim, S Kim, M Lee, J Seok Engineering Applications of Artificial Intelligence 115, 105259, 2022 | 18 | 2022 |
| An ensemble deep learning model with a gene attention mechanism for estimating the prognosis of low-grade glioma M Lee Biology 11 (4), 586, 2022 | 17 | 2022 |
| Estimation with uncertainty via conditional generative adversarial networks M Lee, J Seok Sensors 21 (18), 6194, 2021 | 17 | 2021 |
Junhee SeokProfessor, Korea University, Seoul, South KoreaEmail yang diverifikasi di korea.ac.kr
