Issue #121
July 4, 2021
- 1. Understanding Convolutions on Graphs [distill.pub]
- 2. A Gentle Introduction to Graph Neural Networks [distill.pub]
- 3. Anomaly Detection: Why Your Data Team Is Just Not That Into It [montecarlodata.com]
- 4. How big science failed to unlock the mysteries of the human brain [technologyreview.com]
- 5. Simulating Traffic Flow in Python [towardsdatascience.com]
- 6. Machine Learning With Graphs: Going Beyond Tabular Data [odsc.com]
- 7. Machine Learning to Predict Earnings for Stocks: Support-vector Machines [medium.com/analytics-vidhya]
- • Cognitive maps of social features enable flexible inference in social networks (J.-Y. Son, A. Bhandari, O. F. Hall)
- • Persistence of information flow: A multiscale characterization of human brain (B. Benigni, A. Ghavasieh, A. Corso, V. d’Andrea, M. De Domenico)
- • The global effectiveness of fact-checking: Evidence from simultaneous experiments in Argentina, Nigeria, South Africa, and the United Kingdom (E. Porter, T. J. Wood)
- • Learning Mathematical Properties of Integers (M. Ryskina, K. Knight)
- • The mathematics of adversarial attacks in AI -- Why deep learning is unstable despite the existence of stable neural networks (A. Bastounis, A. C. Hansen, V. Vlačić)
- • LM-Critic: Language Models for Unsupervised Grammatical Error Correction (M. Yasunaga, J. Leskovec, P. Liang)
Enjoy the newsletter?
Forward it to a friend, or subscribe to get it straight to your inbox.
Subscribe Free