Clustering a network with 1.5B edges using the nested SBM in parallel using 256 threads, with the newest @graph-tool.skewed.de version. 🚀

Good news everyone! 🎉 The new version 3.0 of graph-tool is just out with major improvements! See below. graph-tool.skewed.de graph-tool is a comprehensive and efficient Python library to work with networks, including structural, dynamical, and statistical algorithms, as well as visualization. 1/N

Raising a glass to @tiago.skewed.de ‘s amazing @graph-tool.skewed.de which just allowed us to extract all of India’s OSM road network’s ~260 million edges into a smashing largest connected component of ~130 million edges. C++ and graph-tool. Hope we can publish and cite our global analysis soon!🙏🙏🙏🙏

A couple of weeks ago we had our first “Complexity Lab Retreat” at great location in Traunkirchen! skewed.de/lab/group.ht... We had the opportunity to flex our methodological muscles and learn the dark secrets of the C++ internals of @graph-tool.skewed.de! 💀🤘

As usual, our algorithms are freely available as part of the @graph-tool.skewed.de library, with documentation: graph-tool.skewed.de/static/doc/d... Enjoy! N/N

Network reconstruction from dynamics and behavior

In some cases, direct measurements of the edges of a network are either impossible, or can be done only at significant experimental cost. In such situations, we need to infer the network of interactio...

graph-tool.skewed.de

🚨 New paper on ArXiv: “Uncertainty quantification and posterior sampling for network reconstruction” TL;DR; We present an efficient method to sample the entire ensemble of possible network reconstructions that are compatible with an indirect observation, e.g. a dynamics. Short thread: 1/N

Good news for Arch GNU/Linux users! Graph-tool is now available in the main repository! To install it, just do: pacman -S python-graph-tool The days of compiling graph-tool from AUR are over! Rejoice! 🎉

Good news everyone! A new version of graph-tool is just out! @graph-tool.skewed.de graph-tool.skewed.de Graph-tool is a comprehensive and efficient Python library to work with networks, including structural, dynamical, and statistical algorithms, as well as visualization. 1/N #networkscience

Did you know that you install @graph-tool.skewed.de via @condaproject.bsky.social, it will install binaries that are optimized for your specific CPU micro-architecture, including SIMD vectorization, in addition to having OpenMP enabled? It's awesome! Try it out today!