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expanding test suite
a. Work through nan issues in computation of different metrics
- Analyze maps that yield nan values
- Reimplement anything in the base redist package? (not neeeded it appears)
b. Confidence intervals for kl divergence metrics, kde density estimation
- Succeed in implementing a discrete KL approximation (completely unstable for now)
- Or: compute confidence interval from KDE density estimation
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getting more technical in the discussion of our algorithm and thinking about how we can beef that up,
a. Improve python code via any optimizations possible
- Optimize dissimilarity matrix computation (vectorization or in-place modification)
- Find a way to remove the deepcopies at each step
- Maybe using Disjoint-Set datastructre?
- Multiprocessing
b. Write in algorithmic package and provide algorithm runtime
- Add comments
- Add the possibility to specify the thresholding value as an experiment parameter
c. Practical and theoretical (if any) results
- State space being reachable?
- reworking the intro to get rid of some fluff,
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expanding related literature section,
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Ask about publishing and what we need to improve… other stuff
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EAAMO Specifics
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Read through formatting and citation guidelines and implement them
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Read through past years papers to guide relevant editing and problem motivation
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