@xgi.bsky.social in the wild 👀

@xgi.bsky.social in the wild 👀

@nwlandry.bsky.social fighting against vibes-based estimations of the convergence when sampling from the configuration model. Good content. Bonus: @xgi.bsky.social viz

Tim LaRock talking about the number (and properties) of hypergraphs with the same pairwise projection. Very cool work and a picture of @xgi.bsky.social in the wild 👀

Hypergraph Link Prediction via Hyperedge Copying https://arxiv.org/abs/2502.02386 We propose a generative model of temporally-evolving hypergraphs in which hyperedges form via noisy copying of previous hyperedges. Our proposed model reproduces several stylized facts from many empirical hyperg...📈🤖

XGI in the wild!

New release! Version 0.9.5 adds support for hyperedge line width. We also fixed an error in our random generative models and made some methods up to 4x faster (!!!) in the process. @kaiserdaniel.bsky.social also made his first contribution, fixing an error in the hypergraph Laplacian. Thanks Daniel!

XGI in the wild!

Did you know that XGI can load chemical reaction datasets directly from the BiGG repository? bigg.ucsd.edu. Simply run "xgi.load_bigg_data()" and see what datasets are available!

Did you know that XGI offers 39(!) higher-order datasets in a standardized format? xgi.readthedocs.io/en/stable/xg...

Guess what? Now, we have benchmarks for core functionality! Any suggestions for additional benchmarks? xgi-org.github.io/xgi/dev/bench/

X-mas has come early this year for XGI-ers! We are excited to announce massive changes to our documentation, datasets, and functionality! This follows our latest poll (below): see thread below for details 👇🧵

This is the bluesky account for XGI, a Python library for working with higher-order networks! Expect periodic updates on what we're working on, new releases, and research that uses XGI. We're excited to engage with the community here!

Hello, hypergraphy world!