Tim Dockhorn

According to our database, Tim Dockhorn authored at least 14 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space.

Black Forest Labs, Stephen Batifol, Andreas Blattmann, Frederic Boesel, Saksham Consul, Cyril Diagne, Tim Dockhorn, Jack English, Zion English, Patrick Esser, Sumith Kulal, Kyle Lacey, Yam Levi, Cheng Li, Dominik Lorenz, Jonas Müller, Dustin Podell, Robin Rombach, Harry Saini, Axel Sauer, Luke Smith

CoRR, June, 2025

2024

Scaling Rectified Flow Transformers for High-Resolution Image Synthesis.

Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, Dustin Podell, Tim Dockhorn, Zion English, Kyle Lacey, Alex Goodwin, Yannik Marek, Robin Rombach

CoRR, 2024

Fast High-Resolution Image Synthesis with Latent Adversarial Diffusion Distillation.

Axel Sauer, Frederic Boesel, Tim Dockhorn, Andreas Blattmann, Patrick Esser, Robin Rombach

Proceedings of the SIGGRAPH Asia 2024 Conference Papers, 2024

Scaling Rectified Flow Transformers for High-Resolution Image Synthesis.

Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, Dustin Podell, Tim Dockhorn, Zion English, Robin Rombach

Proceedings of the Forty-first International Conference on Machine Learning, 2024

SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, Robin Rombach

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Accelerating and Privatizing Diffusion Models.

Tim Dockhorn

PhD thesis, 2023

Differentially Private Diffusion Models.

Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis

Trans. Mach. Learn. Res., 2023

Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Andreas Blattmann, Tim Dockhorn, Sumith Kulal, Daniel Mendelevitch, Maciej Kilian, Dominik Lorenz, Yam Levi, Zion English, Vikram Voleti, Adam Letts, Varun Jampani, Robin Rombach

CoRR, 2023

Align Your Latents: High-Resolution Video Synthesis with Latent Diffusion Models.

Andreas Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, Karsten Kreis

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

GENIE: Higher-Order Denoising Diffusion Solvers.

Tim Dockhorn, Arash Vahdat, Karsten Kreis

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Score-Based Generative Modeling with Critically-Damped Langevin Diffusion.

Tim Dockhorn, Arash Vahdat, Karsten Kreis

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Demystifying and Generalizing BinaryConnect.

Tim Dockhorn, Yaoliang Yu, Eyyüb Sari, Mahdi Zolnouri, Vahid Partovi Nia

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Density Deconvolution with Normalizing Flows.

Tim Dockhorn, James A. Ritchie, Yaoliang Yu, Iain Murray

CoRR, 2020

2019

A Discussion on Solving Partial Differential Equations using Neural Networks.

Tim Dockhorn

CoRR, 2019