RT @kryssalian@twitter.com

o/ I'm Kryssalian a French pixel artist making loop animations with different durations, so they don't match together 🤓

🐦🔗: twitter.com/kryssalian/status/

We will be offering a limited number of 🚨full scholarships🚨, covering full tuition waiver and housing aid.

The program is hosted by @dnds_ceu@twitter.com at @ceu@twitter.com, in Vienna 🇦🇹, often ranked the most livable city in the world.

Deadlines: Feb. 1, Apr. 12, 2021

Spread the word!


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Exciting news! We are announcing a new undergraduate program in Quantitative Social Sciences at @dnds_ceu@twitter.com.


Our program combines rigorous ("hard sciences"-level) mathematics, statistics, and programming with the pillars of the social sciences. 1/3

New version of graph-tool is out!

(New: graph-tool.skewed.de/static/do)

Single-line install instructions:

Anaconda ⤵️
conda create --name gt -c conda-forge graph-tool

Homebrew ⤵️
brew install graph-tool

apt-get install python3-graph-tool

RT @tiagopeixoto@twitter.com

I'm happy to announce a new project, called Netzschleuder: networks.skewed.de

This is a network data catalogue and repository. It currently contains 257 datasets totaling 3,916 individual networks (94,956 if you include a big @openstreetmap@twitter.com trove).

🐦🔗: twitter.com/tiagopeixoto/statu

Ok, the Conan sword was cool.

RT @Schwarzenegger@twitter.com

My message to my fellow Americans and friends around the world following this week's attack on the Capitol.

🐦🔗: twitter.com/Schwarzenegger/sta

New on the @arxiv_physics: "Disentangling homophily, community structure and triadic closure in networks", arxiv.org/abs/2101.02510

Homophily/communities and triadic closure (triangles) are conflated properties in network analysis, and this method tells them apart.

New work on the arxiv: "Network reconstruction and community detection from dynamics",

I show how coupling Bayesian network reconstruction from functional behavior with community detection enhances both tasks simultaneously.

Just out on PRX: "Reconstructing Networks with Unknown and Heterogeneous Errors"

New method can reconstruct networks and provide error estimates for them, even when measurement uncertainties are unknown.


Code is available as part of graph-tool: graph-tool.skewed.de :gt:

The documentation for the reconstruction code is here: graph-tool.skewed.de/static/do

Each integer is represented in a high-dimensional space, and gets squished down to 2D so that numbers with similar prime factorisations are closer together than those with dissimilar factorisations.


Via @svscarpino@twitter.com.

Finally on the arXiv: "Reconstructing networks with unknown and heterogeneous errors" arxiv.org/abs/1806.07956

Did you know you can reconstruct and make error estimates for networks, by making only a single noisy measurement?

Mastodon @ skewed.de

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