| Sdxl: Improving latent diffusion models for high-resolution image synthesis D Podell, Z English, K Lacey, A Blattmann, T Dockhorn, J Müller, J Penna, ... arXiv preprint arXiv:2307.01952, 2023 | 926 | 2023 |
| Align your latents: High-resolution video synthesis with latent diffusion models A Blattmann, R Rombach, H Ling, T Dockhorn, SW Kim, S Fidler, K Kreis Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 638 | 2023 |
| Stable video diffusion: Scaling latent video diffusion models to large datasets A Blattmann, T Dockhorn, S Kulal, D Mendelevitch, M Kilian, D Lorenz, ... arXiv preprint arXiv:2311.15127, 2023 | 344 | 2023 |
| Score-based generative modeling with critically-damped langevin diffusion T Dockhorn, A Vahdat, K Kreis arXiv preprint arXiv:2112.07068, 2021 | 222 | 2021 |
| Scaling rectified flow transformers for high-resolution image synthesis P Esser, S Kulal, A Blattmann, R Entezari, J Müller, H Saini, Y Levi, ... Forty-first International Conference on Machine Learning, 2024 | 175 | 2024 |
| Genie: Higher-order denoising diffusion solvers T Dockhorn, A Vahdat, K Kreis Advances in Neural Information Processing Systems 35, 30150-30166, 2022 | 86 | 2022 |
| Differentially private diffusion models T Dockhorn, T Cao, A Vahdat, K Kreis arXiv preprint arXiv:2210.09929, 2022 | 77 | 2022 |
| A discussion on solving partial differential equations using neural networks T Dockhorn arXiv preprint arXiv:1904.07200, 2019 | 72 | 2019 |
| Fast high-resolution image synthesis with latent adversarial diffusion distillation A Sauer, F Boesel, T Dockhorn, A Blattmann, P Esser, R Rombach arXiv preprint arXiv:2403.12015, 2024 | 31 | 2024 |
| Latent space diffusion models of cryo-EM structures K Kreis, T Dockhorn, Z Li, E Zhong arXiv preprint arXiv:2211.14169, 2022 | 14 | 2022 |
| Density deconvolution with normalizing flows T Dockhorn, JA Ritchie, Y Yu, I Murray arXiv preprint arXiv:2006.09396, 2020 | 7 | 2020 |
| Demystifying and generalizing binaryconnect T Dockhorn, Y Yu, E Sari, M Zolnouri, V Partovi Nia Advances in Neural Information Processing Systems 34, 13202-13216, 2021 | 5 | 2021 |
| Generative machine learning models for privacy preserving synthetic data generation using diffusion KJ Kreis, T Dockhorn, T Cao, A Vahdat US Patent App. 18/164,215, 2024 | 1 | 2024 |
| Synthesizing content using diffusion models in content generation systems and applications KJ Kreis, T Dockhorn, A Vahdat US Patent App. 18/319,986, 2023 | 1 | 2023 |
| High-resolution video generation using image diffusion models KJ Kreis, R Rombach, A Blattmann, SW Kim, H Ling, S Fidler, T Dockhorn US Patent App. 18/181,729, 2024 | | 2024 |
| Accelerating and Privatizing Diffusion Models T Dockhorn University of Waterloo, 2023 | | 2023 |
| Diffusion-based generative modeling for synthetic data generation systems and applications K Kreis, T Dockhorn, A Vahdat US Patent App. 17/959,915, 2023 | | 2023 |
| Distilling the knowledge in diffusion models T Dockhorn, R Rombach, A Blatmann, Y Yu CVPR Workshop Generative Modelsfor Computer Vision 2 (3), 2023 | | 2023 |
| Generative Modeling with Neural Ordinary Differential Equations T Dockhorn University of Waterloo, 2019 | | 2019 |
