Phil 4.15.20

Fix siding from wind!

D20

  • Talked to Aaron about taking a derivative of the regression slope to see what it looks like. There may be common features in the pattern of rates, or of the slopes of the regressions changing over time
  • Still worried about countries that don’t report well. I’d like to be able to use rates from neighboring countries as some kind of check
  • Got the first pass on a world map json file done
  • Spread of SARS-CoV-2 in the Icelandic Population
    • As of April 4, a total of 1221 of 9199 persons (13.3%) who were recruited for targeted testing had positive results for infection with SARS-CoV-2. Of those tested in the general population, 87 (0.8%) in the open-invitation screening and 13 (0.6%) in the random-population screening tested positive for the virus. In total, 6% of the population was screened. Most persons in the targeted-testing group who received positive tests early in the study had recently traveled internationally, in contrast to those who tested positive later in the study. Children under 10 years of age were less likely to receive a positive result than were persons 10 years of age or older, with percentages of 6.7% and 13.7%, respectively, for targeted testing; in the population screening, no child under 10 years of age had a positive result, as compared with 0.8% of those 10 years of age or older. Fewer females than males received positive results both in targeted testing (11.0% vs. 16.7%) and in population screening (0.6% vs. 0.9%). The haplotypes of the sequenced SARS-CoV-2 viruses were diverse and changed over time. The percentage of infected participants that was determined through population screening remained stable for the 20-day duration of screening.

ACSOS

  • Finished first pass of the lit review. Now at 13 pages

GOES

  • Start looking at GANs. Also work on fixing Optevolver for multiple CPUs
    • Starting Deep Learning with TensorFlow 2 and Keras: Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API, 2nd Edition. Chapter six is GANs, which is what I’m interested in, but I’m ok with getting some review in first.
    • Working on embeddings with the IMDB sentiment analysis project. It’s the first time I’ve seen an embedding layer which is 1) Cool, and 2) Something to play with. I’d noticed when I was working with Word2Vec for my research that embeddings didn’t seem to change shape much as a function of the number of dimensions. It seemed like a lot of information was being kept at very low dimensions, like three, rather than the more accepted 128 or so:

place-embeddings

    • Well, this example gave me an opportunity to test that with some accuracy numbers. Here’s what I get:

EmbeddingDimensions

    • That is super interesting. It basically means that model building, testing, and visualization can happen at low dimensions. That makes everything faster, and with about a 10% improvement likely as one of the last steps.
    • Continuing with book.
  • Wrote up a response to Mike M’s questions about the white paper. Probably pointless, and has pretty much wasted my afternoon. And it was pointless! Now what?
  • Slides for John?

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