| Understanding the latent space of diffusion models through the lens of riemannian geometry YH Park, M Kwon, J Choi, J Jo, Y Uh Advances in Neural Information Processing Systems 36, 24129-24142, 2023 | 50 | 2023 |
| Unsupervised discovery of semantic latent directions in diffusion models YH Park, M Kwon, J Jo, Y Uh arXiv preprint arXiv:2302.12469, 2023 | 21 | 2023 |
| Direct unlearning optimization for robust and safe text-to-image models YH Park, S Yun, JH Kim, J Kim, G Jang, Y Jeong, J Jo, G Lee arXiv preprint arXiv:2407.21035, 2024 | 8 | 2024 |
| Upsample guidance: Scale up diffusion models without training J Hwang, YH Park, J Jo arXiv preprint arXiv:2404.01709, 2024 | 7 | 2024 |
| Geometric Remove-and-Retrain (GOAR): Coordinate-Invariant eXplainable AI Assessment YH Park, J Seo, B Park, S Lee, J Jo arXiv preprint arXiv:2407.12401, 2024 | 1 | 2024 |
| DECOR: Decomposition and Projection of Text Embeddings for Text-to-Image Customization G Jang, JH Kim, YH Park, J Kim, G Lee, Y Jeong arXiv preprint arXiv:2412.09169, 2024 | | 2024 |
| $\textit {Jump Your Steps} $: Optimizing Sampling Schedule of Discrete Diffusion Models YH Park, CH Lai, S Hayakawa, Y Takida, Y Mitsufuji arXiv preprint arXiv:2410.07761, 2024 | | 2024 |
| : Optimizing Sampling Schedule of Discrete Diffusion Models YH Park, CH Lai, S Hayakawa, Y Takida, Y Mitsufuji CoRR, 2024 | | 2024 |
| Resolution Chromatography of Diffusion Models J Hwang, YH Park, J Jo arXiv preprint arXiv:2401.10247, 2023 | | 2023 |
| Diffusion Unlearning Optimization for Robust and Safe Text-to-Image Models YH Park, S Yun, JH Kim, J Kim, G Jang, Y Jeong, J Jo, G Lee | | |
