Issue #114
July 4, 2021
- 1. Dimensionality reduction in neural data analysis [xcorr.net]
- 2. A.I. Predicts the Shapes of Molecules to Come [nytimes.com]
- 3. Hundreds of AI tools have been built to catch covid. None of them helped [technologyreview.com]
- 4. A blood marker predicts who gets ‘breakthrough’ COVID [nature.com]
- 5. The Consistent Estimator [towardsdatascience.com]
- 6. Learning to Extrapolate with Generative AI Models [blog.einstein.ai]
- 7. Python PDF Handling Tutorial [github.com/prajwollamichhane11]
- 8. A Natural Language Processing (NLP) Primer [towardsdatascience.com]
- 9. Building intuition for p-values and statistical significance [bytepawn.com]
- 10. Machine-learning on dirty data in Python: a tutorial [dirtydata.science]
- • Historical language records reveal a surge of cognitive distortions in recent decades (J. Bollen, M. ten Thij, F. Breithaupt, A. T. J. Barron, L. A. Rutter, L. Lorenzo-Luaces, M. Scheffer)
- • Mobility patterns are associated with experienced income segregation in large US cities (E. Moro, D. Calacci, X. Dong, A. Pentland)
- • Privacy implications of accelerometer data: a review of possible inferences (J. L. Kröger, P. Raschke, T. R. Bhuiyan)
- • How epidemic psychology works on Twitter: evolution of responses to the COVID-19 pandemic in the U.S. (L. M. Aiello, D. Quercia, K. Zhou, M. Constantinides, S. Šćepanović, S. Joglekar)
- • Individual-driven versus interaction-driven burstiness in human dynamics: The case of Wikipedia edit history (J. Choi, T. Hiraoka, and H.-H. Jo)
- • Geospatial Model of COVID-19 Spreading and Vaccination With Event Gillespie Algorithm (A. Temerev, L. Rozanova, J. Estill, O. Keiser)
- • Hiding in Temporal Networks (M. Waniek, P. Holme, T. Rahwan)
- • On node ranking in graphs (E. Dudkina, M. Bin, J. Breen, E. Crisostomi, P. Ferraro, S. Kirkland, J. Marecek, R. Murray-Smith, T. Parisini, L. Stone, S. Yilmaz, R. Shorten)
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