Issue #79
November 29, 2020
- 1. A Helping of Science With Your Thanksgiving Dinner [nytimes.com]
- 2. SQLite as a document database [dgl.cx]
- 3. Spatial Computing Could Be the Next Big Thing [scientificamerican.com]
- 4. How Misinformation ‘Superspreaders’ Seed False Election Theories [nytimes.com]
- 5. Landmark Papers in Machine Learning [github.com/daturkel]
- 6. Maximum Likelihood (ML) vs. REML [towardsdatascience.com]
- 7. Learning Causal Models [medium.com/@sgrimbly]
- 8. Interpretability in Machine Learning: An Overview [thegradient.pub]
- • The science of deep learning (R. Baraniuk, D. Donoho, M. Gavish)
- • The brain produces mind by modeling (R. M. Shiffrin, D. S. Bassett, N. Kriegeskorte, J. B. Tenenbaum)
- • How humans learn and represent networks (C. W. Lynn, D. S. Bassett)
- • Stablecoins: risks, potential and regulation (D. Arner, R. Auer, J. Frost)
- • Artificial intelligence and thermodynamics help solving arson cases (S. Korver, E. Schouten, O. A. Moultos, P. Vergeer, M. M. P. Grutters, L. J. C. Peschier, T. J. H. Vlugt, M. Ramdin)
- • Scientists are harnessing viruses to treat tumours (C. Brown)
- • Time Series Data Imputation: A Survey on Deep Learning Approaches (C. Fang, C. Wang)
- • Causal inference using deep neural networks (Y. Yuan, X. Ding, Z. Bar-Joseph)
- • Data Mining Techniques in Predicting Breast Cancer (H. Saad, N. Nagarur)
- • What do we expect from Multiple-choice QA Systems? (K. Shah, N. Gupta, D. Roth)
JAX: accelerated machine learning research via composable function transformations in Python
All our videos are also available in our YouTube playlist.
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