#PortfolioDay o/ I'm Kryssalian a French pixel artist making loop animations with different durations, so they don't match together 🤓
#CSHVienna is happy and proud to call
Central European University @firstname.lastname@example.org
a new member! 🗣️
Rage Against the Vaccine
We will be offering a limited number of 🚨full scholarships🚨, covering full tuition waiver and housing aid.
The program is hosted by @email@example.com at @firstname.lastname@example.org, in Vienna 🇦🇹, often ranked the most livable city in the world.
Deadlines: Feb. 1, Apr. 12, 2021
Spread the word!
Exciting news! We are announcing a new undergraduate program in Quantitative Social Sciences at @email@example.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!
Single-line install instructions:
conda create --name gt -c conda-forge graph-tool
brew install graph-tool
apt-get install python3-graph-tool
I'm happy to announce a new project, called Netzschleuder: https://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 @firstname.lastname@example.org trove).
Ok, the Conan sword was cool.
My message to my fellow Americans and friends around the world following this week's attack on the Capitol.
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: https://graph-tool.skewed.de
The documentation for the reconstruction code is here: https://graph-tool.skewed.de/static/doc/demos/inference/inference.html#network-reconstruction
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.
Finally on the arXiv: "Reconstructing networks with unknown and heterogeneous errors" https://arxiv.org/abs/1806.07956
Did you know you can reconstruct and make error estimates for networks, by making only a single noisy measurement?
Physics & Networks
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