Martin Rosvall
@mrosvall.bsky.social
260 followers 6 following 4 posts
Professor of physics in Integrated Science Lab, IceLab, Umeå University. For the passion of revealing stories in relational data, we study information flows through social and biological systems to comprehend their inner workings.
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Reposted by Martin Rosvall
icelabumu.bsky.social
🌍 One rule may explain how life is organised across ecosystems, from deep oceans to dry savannas.
Rubén Bernardo Madrid IceLab postdoc at @umeauniversitet.bsky.social is first author of a new study in @natecoevo.nature.com identifying this pattern in biodiversity.
www.umu.se/en/news/one-...
One single rule helps explain life on Earth
The discovery will help to understand why species are spread the way they are across the planet.
www.umu.se
mrosvall.bsky.social
Registration is now open for IceLab Camp – a four-day off-site PhD course designed to train participants in asking research questions, laying the foundation for new multidisciplinary collaborations. www.umu.se/en/icelab/ca...
IceLab Camp
Part of the Stress Response Modeling Research School, IceLab Camp is a four-day off-site PhD course that prepares its participants to create new inter- or multidisciplinary research by first teaching ...
www.umu.se
Reposted by Martin Rosvall
icelabumu.bsky.social
🕒🌲 New study in npj Biological Timing and Sleep led by IceLab multidisciplinary postdoc Bertold Mariën reveals that adjusting trees' internal clocks can help them better cope with climate change. Read more: www.umu.se/en/news/adju... Unspool 🧵for main findings 👇 #PlantScience #ClimateAdaptation
Adjusting trees’ internal clocks can help them cope with climate change
Study shows adjusting trees’ internal clocks could help them cope with climate change
www.umu.se
mrosvall.bsky.social
We claim that insights from network science can advance deep graph learning in arxiv.org/abs/2502.01177 A fun and enlightening collaboration with Chris Blöcker, Ingo Scholtes, and @jevinwest.bsky.social
Illustrative example of how network science insights can advance deep graph learning.
mrosvall.bsky.social
We construct concise networks from path
data. Interpolating between first and second-order models, the networks capture critical memory effects using a minimal number of interpretable state nodes. Great collaboration with @is-this-rohit.bsky.social and @lambiotte.bsky.social arxiv.org/pdf/2501.08302
Method schematic.