| Spiking-yolo: spiking neural network for energy-efficient object detection S Kim, S Park, B Na, S Yoon Proceedings of the AAAI conference on artificial intelligence 34 (07), 11270 …, 2020 | 463 | 2020 |
| Autosnn: Towards energy-efficient spiking neural networks B Na, J Mok, S Park, D Lee, H Choe, S Yoon International Conference on Machine Learning, 16253-16269, 2022 | 82 | 2022 |
| DNA-level splice junction prediction using deep recurrent neural networks B Lee, T Lee, B Na, S Yoon arXiv preprint arXiv:1512.05135, 2015 | 56 | 2015 |
| AdvRush: Searching for adversarially robust neural architectures J Mok, B Na, H Choe, S Yoon Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 48 | 2021 |
| Spiking-yolo: Spiking neural network for real-time object detection S Kim, S Park, B Na, S Yoon arXiv preprint arXiv:1903.06530 1, 2019 | 36 | 2019 |
| Privacy-preserving deep sequential model with matrix homomorphic encryption J Jang, Y Lee, A Kim, B Na, D Yhee, B Lee, JH Cheon, S Yoon Proceedings of the 2022 ACM on Asia Conference on Computer and …, 2022 | 25 | 2022 |
| Towards fast and accurate object detection in bio-inspired spiking neural networks through Bayesian optimization S Kim, S Park, B Na, J Kim, S Yoon IEEE Access 9, 2633-2643, 2020 | 24 | 2020 |
| Accelerating neural architecture search via proxy data B Na, J Mok, H Choe, S Yoon arXiv preprint arXiv:2106.04784, 2021 | 21 | 2021 |
| Demystifying the neural tangent kernel from a practical perspective: Can it be trusted for neural architecture search without training? J Mok, B Na, JH Kim, D Han, S Yoon Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 15 | 2022 |
| Ultrafast prediction of somatic structural variations by filtering out reads matched to pan-genome k-mer sets J Sohn, MH Choi, D Yi, VA Menon, YJ Kim, J Lee, JW Park, S Kyung, ... Nature Biomedical Engineering 7 (7), 853-866, 2023 | 5 | 2023 |
| Memory-augmented neural networks on FPGA for real-time and energy-efficient question answering S Park, J Jang, S Kim, B Na, S Yoon IEEE Transactions on Very Large Scale Integration (VLSI) Systems 29 (1), 162-175, 2020 | 5 | 2020 |
| Scalable smartphone cluster for deep learning B Na, J Jang, S Park, S Kim, J Kim, MS Jeong, KC Kim, S Heo, Y Kim, ... arXiv preprint arXiv:2110.12172, 2021 | 4 | 2021 |
| Benchmark of machine learning force fields for semiconductor simulations: datasets, metrics, and comparative analysis G Kim, B Na, G Kim, H Cho, S Kang, HS Lee, S Choi, H Kim, S Lee, Y Kim Advances in Neural Information Processing Systems 36, 51434-51476, 2023 | 3 | 2023 |
| Variance-stationary differentiable NAS H Choe, B Na, J Mok, S Yoon architecture 3 (10), 16-20, 2021 | 3 | 2021 |
| Personalized face authentication based on few-shot meta-learning C Shin, J Lee, B Na, S Yoon 2021 IEEE International Conference on Image Processing (ICIP), 3897-3901, 2021 | 2 | 2021 |
| Ultra-fast Prediction of Somatic Structural Variations by Reduced Read Mapping via Pan-Genome k-mer Sets MH Choi, J Sohn, D Yi, AV Menon, YJ Kim, S Kyung, SH Shin, B Na, ... bioRxiv, 2020.10. 25.354456, 2020 | 2 | 2020 |
| An Applicability Study on Parallel Computing for webOS-based Smart TV Y Jeon, D Koo, B Na, S Yoon Proceedings of the Korea Information Processing Society Conference, 336-339, 2014 | 1 | 2014 |
| Author Correction: AIVariant: a deep learning-based somatic variant detector for highly contaminated tumor samples H Jeon, J Ahn, B Na, S Hong, L Sael, S Kim, S Yoon, D Baek Experimental & Molecular Medicine, 1-1, 2025 | | 2025 |
| AIVariant: a deep learning-based somatic variant detector for highly contaminated tumor samples H Jeon, J Ahn, B Na, S Hong, L Sael, S Kim, S Yoon, D Baek Experimental & Molecular Medicine 55 (8), 1734-1742, 2023 | | 2023 |
| Notice of Retraction: E2V-SDE: From Asynchronous Events to Fast and Continuous Video Reconstruction via Neural Stochastic Differential Equations J Kim, DJ Lee, B Na, S Park, J Jo, S Yoon 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR …, 2022 | | 2022 |
