| Improving Low-Latency Predictions in Multi-Exit Neural Networks via Block-Dependent Losses DJ Han, J Park, S Ham, N Lee, J Moon IEEE Transactions on Neural Networks and Learning Systems, 2023 | 3 | 2023 |
| NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks S Ham, J Park, DJ Han, J Moon Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| Training Multi-Exit Architectures via Block-Dependent Losses for Anytime Inference DJ Han, JW Park, S Ham, N Lee, J Moon 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition …, 2022 | 1 | 2022 |
| Switch Diffusion Transformer: Synergizing Denoising Tasks with Sparse Mixture-of-Experts B Park, H Go, JY Kim, S Woo, S Ham, C Kim arXiv preprint arXiv:2403.09176, 2024 | | 2024 |
| Knowledge distillation based adversarial training for robust multi-exit neural network S Ham 한국과학기술원, 2023 | | 2023 |
Dong-Jun HanPurdue Universitypurdue.edu의 이메일 확인됨
