Issue #127
July 4, 2021
- 1. A First-Principles Theory of Neural Network Generalization [bair.berkeley.edu]
- 2. How to deploy machine learning with differential privacy? [differentialprivacy.org]
- 3. How AI is reinventing what computers are [technologyreview.com]
- 4. The Age of Machine Learning As Code Has Arrived [huggingface.co]
- 5. SHAP: Explain Any Machine Learning Model in Python [towardsdatascience.com]
- 6. Reflections on Foundation Models [thegradient.pub]
- • The interplay between communities and homophily in semi-supervised classification using graph neural networks (H. Hussain, T. Duricic, E. Lex, D. Helic, R. Kern)
- • Universal patterns of long-distance commuting and social assortativity in cities (E. Bokányi, S. Juhász, M. Karsai, B. Lengyel)
- • Node-based Generalized Friendship Paradox fails (A. Evtushenko, J. Kleinberg)
- • Non-deep Networks (A. Goyal, A. Bochkovskiy, J. Deng, V. Koltun)
- • SciCap: Generating Captions for Scientific Figures (T.-Y. Hsu, C. L. Giles, T.-H. Huang)
- • Robustness modularity in complex networks (F. N. Silva, A. Albeshri, V. Thayananthan, W. Alhalabi, S. Fortunato)
- • Comparison of Indicators of Location Homophily Using Twitter Follow Graph (S. Hironaka, M. Yoshida, K. Umemura)
- • Learning Time-Varying Graphs from Online Data (A. Natali, E. Isufi, M. Coutino, G. Leus)
Introduction to NetworkX in Python
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