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tasty diffusion papers - september 2024

OmniGen: Unified Image Generation
what: one transformer for the text-to-image diffusion model.
- rectified flow.
- multimodal condition: text and image.
- one model processes all context and does diffusion steps.

Diffusion Policy Policy Optimization
what: set of best practices for fine-tuning diffusion-based policies in continuous control and robot learning tasks.

Rejection Sampling IMLE: Designing Priors for Better Few-Shot Image Synthesis
what: modification which helps to generalize better on few samples.

my thoughts
- i like how AI community is trying to simplify everything. surprisingly sometimes it works well. for example, rectified flow is simplified version of diffusion.
- rl + diffusion => next step in brain stimulation?
diffusion models could mimic brain patterns for smoother stimulation. with RL, they’d adapt in real-time, making treatments more precise and personalized. shifting from rigid protocols to dynamic brain interventions.

#digest



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tasty diffusion papers - september 2024

OmniGen: Unified Image Generation
what: one transformer for the text-to-image diffusion model.
- rectified flow.
- multimodal condition: text and image.
- one model processes all context and does diffusion steps.

Diffusion Policy Policy Optimization
what: set of best practices for fine-tuning diffusion-based policies in continuous control and robot learning tasks.

Rejection Sampling IMLE: Designing Priors for Better Few-Shot Image Synthesis
what: modification which helps to generalize better on few samples.

my thoughts
- i like how AI community is trying to simplify everything. surprisingly sometimes it works well. for example, rectified flow is simplified version of diffusion.
- rl + diffusion => next step in brain stimulation?
diffusion models could mimic brain patterns for smoother stimulation. with RL, they’d adapt in real-time, making treatments more precise and personalized. shifting from rigid protocols to dynamic brain interventions.

#digest

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