Issue #60
July 19, 2020
- 1. Entropy: An Introduction [homes.cs.washington.edu]
- 2. Data Structures & Algorithms I Actually Used Working at Tech Companies [blog.pragmaticengineer.com]
- 3. Giving GPT-3 a Turing Test [lacker.io]
- 4. How We Built Size.link [engineering.shopify.com]
- 5. The Mathematics of Mass Testing for COVID-19 [sinews.siam.org]
- 6. Toward trusted sensing for the cloud: Introducing Project Freta [microsoft.com]
- 7. The Second Wave of Algorithmic Accountability [lpeblog.org]
- • The Computational Limits of Deep Learning (N. C. Thompson, K. Greenewald, K. Lee, G. F. Manso)
- • Susceptible supply limits the role of climate in the early SARS-CoV-2 pandemic (R. E. Baker, W. Yang, G. A. Vecchi, C. J. E. Metcalf, B. T. Grenfell)
- • Predicting mortality from 57 economic, behavioral, social, and psychological factors (E. Puterman, J. Weiss, B. A. Hives, A. Gemmill, D. Karasek, W. B. Mendes, D. H. Rehkopf)
- • Data-driven contact structures: From homogeneous mixing to multilayer networks (A. Aleta, G. Ferraz de Arruda, Y. Moreno)
- • Immunization strategies in networks with missing data (S. F. Rosenblatt, J. A. Smith, G. R. Gauthier, L. Hébert-Dufresne)
- • Learning Graph Structure With A Finite-State Automaton Layer (D. D. Johnson, H. Larochelle, D. Tarlow)
- • Inductive Link Prediction for Nodes Having Only Attribute Information (Y. Hao, X. Cao, Y. Fang, X. Xie, S. Wang)
- • A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results (B. Coker, C. Rudin, G. King)
- • Bayesian Modeling of COVID-19 Positivity Rate -- the Indiana experience (B. Boukai, J. Wang)
- • A Survey on Transfer Learning in Natural Language Processing (Z. Alyafeai, M. S. AlShaibani, I. Ahmad)
Judea Pearl -- The Foundations of Causal Inference [The Book of WHY]
All our videos are also available in our YouTube playlist.
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