Interested in Information processing in biological or social systems? Quantum information? Brain-inspired computing? Open Call for students with interest in obtaining a Ph.D. on these topics. Submissions until 21/9. More detailed information available in: https://t.co/LFxe2EgggI

🎬 https://youtu.be/hftuQXPqfRA

🌀 http://www1.icsi.berkeley.edu/~kfount/post/fractional_programming_and_local_graph_clustering/

🍄 https://researchtheheadlines.org/2018/09/10/talking-headlines-simon-fisher/

📝 Attack Tolerance of Link Prediction Algorithms: How to Hide Your Relations in a Social Network

Study of the ability to alter connections so as to increase the probability that some connections remain unidentified by link prediction algorithms.

🌐 https://arxiv.org/abs/1809.00152

🎲 @ComplexSys

📝 "Mathematical models of collective dynamics and self-organization" (by P. Degond):

"In this paper, we begin by reviewing a certain number of mathematical challenges posed by the modelling of collective dynamics and self-organization. Then..."

🌐 https://arxiv.org/abs/1809.02808

🎲 @ComplexSys

🎬 https://youtu.be/DilOZ7s07w0

This is how Google Translate is trained to be biased in gender neutral languages like Persian.
And this paper shows that the bias is even more than the real data!
https://t.co/2TVXLNTgqt

🌀 https://www.newsweek.com/bilingual-brain-heres-what-happens-when-you-flip-between-languages-1111264?amp=1&__twitter_impression=true

🌀 http://www.complexity-explorables.org/explorables/strange/

👥 https://theconversation.com/amp/game-theory-can-help-prevent-disease-outbreaks-102934?__twitter_impression=true

🎊 Great summary of Python basics for scientific computing.

http://cs231n.github.io/python-numpy-tutorial/

🌄 Are mountains fractal? Actually there are two scaling regimes (same on earth and venus!)
http://necsi.edu/research/multiscale/earth-venus

Smooth at fine scale, rough at large scales with an exponent satisfying the KPZ (Kardar Parisi Zhang) prediction 0.4.

📝Turn off your e-mail and social media to get more done
Distractions are a fundamental aspect of the modern world, but we don’t have to become hermits to avoid them.

🌐 https://www.nature.com/articles/d41586-018-06213-7

🎲 @ComplexSys

🌀 https://arogozhnikov.github.io/2016/12/19/markov_chain_monte_carlo.html

💡 https://towardsdatascience.com/when-bayes-ockham-and-shannon-come-together-to-define-machine-learning-96422729a1ad

🔖 Triangulating War: Network Structure and the Democratic Peace

Benjamin Campbell, Skyler Cranmer, Bruce Desmarais

🔗 https://arxiv.org/pdf/1809.04141

📌 ABSTRACT
Decades of research has found that democratic dyads rarely exhibit violent tendencies, making the democratic peace arguably the principal finding of Peace Science. However, the democratic peace rests upon a dyadic understanding of conflict. Conflict rarely reflects a purely dyadic phenomena---even if a conflict is not multi-party, multiple states may be engaged in distinct disputes with the same enemy. We postulate a network theory of conflict that treats the democratic peace as a function of the competing interests of mixed-regime dyads and the strategic inefficiencies of fighting with enemies' enemies. Specifically, we find that a state's decision to engage in conflict with a target state is conditioned by the other states in which the target state is in conflict. When accounting for this network effect, we are unable to find support for the democratic peace. This suggests that the major finding of three decades worth of conflict research is spurious.

📝Is together better? Examining scientific collaborations across multiple authors, institutions, and departments

🌐 https://arxiv.org/abs/1809.04093

🎲 @ComplexSys