Issue #126
July 4, 2021
- 1. How Time Series Databases Work—and Where They Don’t [honeycomb.io]
- 2. A gentle introduction to the FFT [earlevel.com]
- 3. The Uselessness of Useful Knowledge [quantamagazine.org]
- 4. Bayesian histograms for rare event classification [dionhaefner.github.io]
- 5. Time Series Forecasting in Python [pub.towardsai.net]
- 6. SHAP: Explain Any Machine Learning Model in Python [towardsdatascience.com]
- 7. Image Encoders: BigTransfer vs CLIP [blog.alexcg.net]
- • What (Exactly) is Novelty in Networks? Unpacking the Vision Advantages of Brokers, Bridges, and Weak Ties (S. Aral, P. S. Dhillon)
- • From temporal network data to the dynamics of social relationships (V. Gelardi, D. Le Bail, A. Barrat, N. Claidiere)
- • Mapping the NFT revolution: market trends, trade networks, and visual features (M. Nadini, L. Alessandretti, F. Di Giacinto, M. Martino, L. M. Aiello, A. Baronchelli)
- • Finding disease outbreak locations from human mobility data (F. Schlosser, D. Brockmann)
- • An Introduction to Probabilistic Programming (J.-W. van de Meent, B. Paige, H. Yang, F. Wood)
- • Scaling of variations in traveling distances and times of taxi routes (X. Feng, H. Sun, B. Gross, J. Wu, D. Li, X. Yang, D. Zhou, Z. Gao, S. Havlin)
- • Knowledge Graphs (A. Hogan, E. Blomqvist, M. Cochez, C. d'Amato, G. de Melo, C. Gutierrez, J. E. L. Gayo, S. Kirrane, S. Neumaier, A. Polleres, R. Navigli, A.-C. N. Ngomo, S. M. Rashid, A. Rula, L. Schmelzeisen, J. Sequeda, S. Staab, A. Zimmermann)
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