vault backup: 2024-09-30 21:09:33

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Dane Sabo 2024-09-30 21:09:33 -04:00
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@ -83,4 +83,6 @@ Point: We look to generative models to accelerate perturbed plant generation.
The goal of this research is to use a generative diffusion model to create unstructured perturbations of a nominal plant.
If this research is successful, this diffusion model will accomplish three main tasks:
**Outcome 1:** Approximate a set of controllable plants by generating a large number of perturbed examples. This research will use the lossy nature of the diffusion model to create the perturbation. The diffusion model
**Outcome 1:** Approximate a set of controllable plants by generating a large number of perturbed examples. This research will use the lossy nature of the diffusion model to create the perturbation. Inference of these models is relatively cheap, while maintaining the ability to create novel samples.
**Outcomes 2:** Perturb a nominal plant in an unstructured manner with a controllable amount of uncertainty.