Issue #82
December 20, 2020
- 1. The Hypersim Dataset [github.com/apple]
- 2. Hypercore is a distributed append-only log [hypercore-protocol.org]
- 3. Is deep learning a new kind of programming? [tomasp.net]
- 4. Understanding mRNA COVID-19 Vaccines [cdc.gov]
- 5. Geospatial Indexing with Uber’s H3 [towardsdatascience.com]
- 6. Stripe’s payments APIs: the first ten years [stripe.com]
- 7. The History of Data Exchange [dolthub.com]
- 8. To the brain, reading computer code is not the same as reading language [news.mit.edu]
- 9. NeurIPS 2020 Papers: Takeaways for a Deep Learning Engineer [towardsdatascience.com]
- 10. Advanced Data Science 2020 [jtleek.com]
- • Understanding adversarial examples requires a theory of artefacts for deep learning (C. Buckner)
- • Computing Graph Neural Networks: A Survey from Algorithms to Accelerators (S. Abadal, A. Jain, R. Guirado, J. López-Alonso, E. Alarcón)
- • mRNA's next challenge: Will it work as a drug? (K. Servick)
- • Estimating tie strength in social networks using temporal communication data (J. Ureña-Carrion, J. Saramäki, M. Kivelä)
- • Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations (P. W. G. Tennant, E. J. Murray, K. F. Arnold, L. Berrie, M. P. Fox, S. C. Gadd, W. J. Harrison, C. Keeble, L. R. Ranker, J. Textor, G. D. Tomova, M. S. Gilthorpe, G. T. H. Ellison)
- • How a torrent of COVID science changed research publishing — in seven charts (H. Else)
- • What are the most important statistical ideas of the past 50 years? (A. Gelman, A. Vehtari)
- • Understanding graph embedding methods and their applications (M. Xu)
- • An Agenda for Disinformation Research (N. Bliss, E. Bradley, J. Garland, F. Menczer, S. W. Ruston, K. Starbird, C. Wiggins)
Markov Chains I
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