Uncertainty Measures in ICF-CycleGAN
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- Python
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Description
Hi Rushil,
Thank you for sharing this interesting work in GitHub. I also have a requirement of using CycleGANs to synthesise simulated data (for a regression problem) matching the distribution of some lab test results and will be citing your work 👍 .
In the presentation of your ICF CycleGAN project by Brian K.Spears, I saw some Bayesian Inference techniques being used to plot some confidence intervals around the predictions (Refer: Slide 25). I like to know what Bayesian Optimization technique is being used here. Could you please add the jupyter notebook or python file demo of these plots with uncertainty measures?
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Research direction
Start by reviewing the existing ICF-CycleGAN project and the uncertainty-measure plots referenced in Slide 25 of the linked presentation. Add a Jupyter notebook or Python demonstration of the Bayesian inference or optimization technique used for the confidence intervals around predictions. Done means the repository contains a runnable example that produces those uncertainty measures.
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Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- data-visualization, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100