Top Tweets for #complexitypapers
Here it goes our last work "Phase transitions and stability of dynamical processes on hypergraphs" (https://t.co/iak6Guhlol), in which we develop a theoretical framework to describe general dynamical processes on arbitrary hypergraphs. Work done with @GuiFdeArruda and M. Tizzani.

#complexitypapers
https://t.co/Y0FVYlpV4D
How can we know if a virus will spread and become pandemic? The standard approach is measuring Ro: the average number of secondary infections. But it turns no to be enough. Network science is required & provides an answer. Here's a great paper by @LHnets
https://t.co/aFgeWYJync

My 1st paper in @PhysRevResearch is just out (https://t.co/uAcf12odxw): we show that not only degree heterogeneity leads to a vanishing epidemic threshold: tuning the recovery rate distribution induces the same qualitative behavior in homogeneous nets! & the opposite is also true

Explosive higher-order Kuramoto dynamics: how topology affects dynamics on links triangles and higher dimensional simplices!
https://t.co/SHfvy1mern

Out today @NatureComms: "Bridging the gap between efficacy trials and model-based impact evaluation for new TB vaccines" We show how results of clinical trials can be used to determine vaccine pathways against disease & evaluate vaccine impact accurately https://t.co/WCcfMDzbJe

Some analytical results and insights on the behavior of 'Random walks on hypergraphs'
https://t.co/UxInTDkcjG
w/ T. Carletti @_giuliacencetti D. Fanelli
@dnds_ceu

#complexitypapers https://t.co/iW6a0dsGtq from the careers of 22K scientists in 4 disciplines, author showed that coauthoring at least *one* paper with a top-cited scientist during the first 3 career years leads to a long-term competitive advantage with respect to peers.
Our first paper on symmetries in biological networks just came up today in Nature Comm:
https://t.co/roVGAjJ0GH
This is a first in a series of papers showing that symmetry groups and symmetry fibrations describe synchronized building blocks in biology.

#complexitypapers a nice mathematical treatment of a simple (only at a first sight) problem https://t.co/H3RiUkfJaM
1/ SciTwitter: I'm very excited to share our new Perspective article out in Nature Neuroscience today!
https://t.co/aYwHN0U0h3
Machine learning and climate change https://t.co/oqLOEMRVIU #complexitypapers

Machine learning and statistical physics “we propose a model machine learning approach that optimizes an effective model based on an estimation of its partition function” https://t.co/xnD9ypqi3H #complexitypapers

Hierarchical organization of urban mobility and its connection with city livability https://t.co/5ZYbwGzr7I #complexitypapers
Large-scale structures in the ΛCDM Universe: network analysis and machine learning. Several fields all together in one paper :)
#complexitypapers https://t.co/gbn0ctfntT

we observed that information diffusion can be detected by link prediction using supervised learning
#complexitypapers
DeepFork: Supervised Prediction of Information Diffusion in GitHub https://t.co/KtwIcsD9U1
latest preprint out: "Span-core Decomposition for Temporal Networks: Algorithms and Applications", https://t.co/LG1Yq6x8O6
with Edoardo Galimberti, Martino Ciaperoni @FrancescoBonchi @alainbarrat Francesco Gullo
Extracting information from documents using deep learning #complexitypapers https://t.co/TnvVgeEjgl @CompSysSoc @YR_CSS
Assessing the interplay between human mobility and mosquito borne diseases in urban environments https://t.co/F0qVvQmfsx #complexitypapers @YR_CSS @CompSysSoc

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