Issue #159
June 12, 2022
- 1. Signatures: The foundations of modern end-to-end encryption [kerkour.com]
- 2. DoWhy evolves to independent PyWhy model to help causal inference grow [microsoft.com]
- 3. The Philosophy of Linear Algebra [sigfyg.medium.com]
- 4. From Python to Numpy [labri.fr]
- 5. Researchers Achieve ‘Absurdly Fast’ Algorithm for Network Flow [quantamagazine.org]
- 6. Techniques for Training Large Neural Networks [openai.com]
- 7. Differentiable Finite State Machines [google-research.github.io]
- • Flat teams drive scientific innovation (F. Xu, L. Wu, J. Evans)
- • Nonparametric Power-Law Surrogates (J. M. Moore, G. Yan, E. G. Altmann)
- • Clone-structured graph representations enable flexible learning and vicarious evaluation of cognitive maps (D. George, R. V. Rikhye, N. Gothoskar, J. S. Guntupalli, A. Dedieu, M. Lázaro-Gredilla)
- • Non-stationary A/B tests (Y. Wu, Z. Zheng, G. Zhang, Z. Zhang, C. Wang)
- • Cooperation among an anonymous group protected Bitcoin during failures of decentralization (A. Blackburn, C. Huber, Y. Eliaz, M. S. Shamim, D. Weisz, G. Seshadri, K. Kim, S. Hang, E. L. Aiden)
- • A Survey on the Fairness of Recommender Systems (Y. Wang, W. Ma, M. Zhang, Y. Liu, S. Ma)
- • Deep Learning Opacity in Scientific Discovery (E. Duede)
- • Socioeconomic biases in urban mixing patterns of US metropolitan areas (R. M. Hilman, G. Iñiguez, M. Karsai)
Airflow DAG: Coding your first DAG for Beginners
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