From b5b1ff01364d83ba0763cf156ac9bd3f5669b17c Mon Sep 17 00:00:00 2001 From: Dane Sabo Date: Mon, 30 Sep 2024 21:09:33 -0400 Subject: [PATCH] vault backup: 2024-09-30 21:09:33 --- 4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md b/4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md index 6aea55af..ef42ae46 100644 --- a/4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md +++ b/4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md @@ -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 \ No newline at end of file +**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. \ No newline at end of file