Issue #133
July 4, 2021
- 1. Mathematicians Transcend Geometric Theory of Motion [quantamagazine.org]
- 2. Training Computer Vision Models on Random Noise Instead of Real Images [unite.ai]
- 3. DeepMind’s AI helps untangle the mathematics of knots [nature.com]
- 4. Apple Neural Engine Internal: From ML Algorithm to HW Registers [blackhat.com]
- 5. AI Training Is Outpacing Moore’s Law [spectrum.ieee.org]]
- 6. Introducing stack graphs [github.blog]
- 7. Prettify Your Data Structures With Pretty Print in Python [realpython.com]
- • Link recommendation algorithms and dynamics of polarization in online social networks (F. P. Santos, Y. Lelkes, S. A. Levin)
- • Polarization and tipping points (M. W. Macy, M. Ma, D. R. Tabin, J. Gao, B. K. Szymanski)
- • What human mobility data tell us about COVID-19 spread (Laura Alessandretti)
- • Companies under stress: the impact of shocks on the production network (R. Pálovics, P. Dolenc, J. Leskovec)
- • Mobility signatures: a tool for characterizing cities using intercity mobility flows (M. Kiashemshaki, Z. Huang, J. Saramäki)
- • Theoretical models and statistical modeling of linguistic epicentres (T. Bernaisch, S. Th. Gries, B. Heller)
- • Opinion dynamics: Public and private (S. Roy, S. Biswas)
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