Refined my haiku visual a little today. I think it would be fun to see if there are any paths to take these words and traverse all of the haiku and if so - how many paths.
The dataset is Creative Commons if anyone wants to fork and play.
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#graphtheory
1 post1 participant0 posts today
A post of @11011110 has reminded me that (after a year and a half lurking here) it's never too late for me to toot and pin an intro here.
I am a Canadian mathematician in the Netherlands, and I have been based at the University of Amsterdam since 2022. I also have some rich and longstanding ties to the UK, France, and Japan.
My interests are somewhere in the nexus of Combinatorics, Probability, and Algorithms. Specifically, I like graph colouring, random graphs, and probabilistic/extremal combinatorics. I have an appreciation for randomised algorithms, graph structure theory, and discrete geometry.
Around 2020, I began taking a more active role in the community, especially in efforts towards improved fairness and openness in science. I am proud to be part of a team that founded the journal, Innovations in Graph Theory (https://igt.centre-mersenne.org/), that launched in 2023. (That is probably the main reason I joined mathstodon!) I have also been a coordinator since 2020 of the informal research network, A Sparse (Graphs) Coalition (https://sparse-graphs.mimuw.edu.pl/), devoted to online collaborative workshops. In 2024, I helped spearhead the MathOA Diamond Open Access Stimulus Fund (https://www.mathoa.org/diamond-open-access-stimulus-fund/).
Until now, my posts have mostly been about scientific publishing and combinatorics.
#introduction
#openscience
#diamondopenaccess
#scientificpublishing
#openaccess
#RemoteConferences
#combinatorics
#graphtheory
#ExtremalCombinatorics
#probability
igt.centre-mersenne.orgInnovations in Graph Theory Innovations in Graph Theory
The Hidden Networks
That Rule Our World
S2 E50
Join us for a fascinating deep dive into the world of network analysis, where we explore Node2Vec - a groundbreaking algorithm that helps us understand the hidden communities within complex networks. Unlock profound insights about communities hidden within the vast connections surrounding us.
https://helioxpodcast.substack.com/p/the-hidden-networks-that-rule-our
#NetworkAnalysis #AI #ComplexSystems #GraphTheory #Node2Vec #NeuralNetworks #SocialNetworks #Podcast
Anyway, I wanted you to know that there's a kind of graph in #mathematics #graphTheory that is called «dessin d'enfant» (child's drawing).
en.wikipedia.orgDessin d'enfant - Wikipedia
Where Graph Theory Meets The Road: The Algorithms Behind Route Planning - Back in the hazy olden days of the pre-2000s, navigating between two locations gen... - https://hackaday.com/2024/04/04/where-graph-theory-meets-the-road-the-algorithms-behind-route-planning/ #transportationhacks #routeplanning #graphtheory #featured #interest #history
Hackaday · Where Graph Theory Meets The Road: The Algorithms Behind Route PlanningBack in the hazy olden days of the pre-2000s, navigating between two locations generally required someone to whip out a paper map and painstakingly figure out the most optimal route between those d…
Hey Mastodon! 
Here is our #introduction post: We are the Data Visualization Lab at Khoury College of Computer Sciences at Northeastern University. You can find more about our work here: https://vis.khoury.northeastern.edu/
We'd love to be connected to more folks and labs in the realms of #DataVisualization #HCI #xAI #AR #VR #VisualAnalytics #PhD #Research
Our lab has been applying visualization to domain areas like #accessibility #UAVs #Genetics #Privacy #Pedagogy #Networks #GraphTheory
Say hi!
vis.khoury.northeastern.eduKhoury Vis Lab, Northeastern UniversityFront page Khoury Vis Lab, Northeastern University
Continued thread
Addendae 4
Graph Structure f. Point Clouds: Geometric Attention All You Need
https://arxiv.org/abs/2307.16662
* partly intersect my interest in knowledge graphs, fully-connected networks, and transformers in NLP and ML
* length of that discussion - though brief - exceeds the Mastodon 500-char limit, so I moved that discussion here:
Fully-connected graphs: Graph neural networks, transformers
https://persagen.com/docs/gnn-transformers.html
arXiv.orgGraph Structure from Point Clouds: Geometric Attention is All You NeedThe use of graph neural networks has produced significant advances in point
cloud problems, such as those found in high energy physics. The question of how
to produce a graph structure in these problems is usually treated as a matter
of heuristics, employing fully connected graphs or K-nearest neighbors. In this
work, we elevate this question to utmost importance as the Topology Problem. We
propose an attention mechanism that allows a graph to be constructed in a
learned space that handles geometrically the flow of relevance, providing one
solution to the Topology Problem. We test this architecture, called
GravNetNorm, on the task of top jet tagging, and show that it is competitive in
tagging accuracy, and uses far fewer computational resources than all other
comparable models.
I still need to add some short blurbs about each chapter, but here's the website for Exploring Graph Theory With Julia, complete with my lazily-designed temporary cover "art": https://leanpub.com/exploring-graph-theory-with-julia
I would love to know if this book sounds interesting to you!
(Boosts welcome 
)
LeanpubExploring Graph Theory With JuliaLearn how the mathematics of relationships helps run the world and explain the universe as you explore the fascinating world of graph theory using the Julia programming language. No advanced math or coding skills required.
Are there any good tools for analysing your Mastodon network in a #GraphTheory / #NetworkAnalysis kind of way?
I'd love to:
- visualise the different groups of people that I follow: what are the connections between the people that I follow?
- see which accounts post a lot, or not at all
- see which accounts I interact with the most (are there people that I followed but it turns out I'm not actually interested in what they post now?)
- see what hours I and others post
Hi folks, I have somebody who is #lookingforajob in the greater #boston area. He’s a PhD in #math with experience doing #graphtheory as well as #quantumcomputing #quantumcompilation. Several yrs of post phd experience in govt looking to get back to #academia and is open to #postdoc or other roles in #research
Lots of new people migrating to Mastodon from Twitter! Given that the crowd is very different here, I thought I'd reintroduce myself by being more open than usual about my recent art.
'⦵ (pour Isidore)' is series of works (including speech synthesis, photography, graph analysis, found artefacts and text) presented across a wav and a pdf. There is no streaming preview.
What kind of #network do we want for #Mastodon (and #Fediverse in general)?
The answer may vary depending on users and communities, but let's discuss where the new follow-recommendation tool of Mastodon 3.5 leads us (https://github.com/mastodon/mastodon/pull/15945).
The evolution of a network where new users preferentially follow existing influencers can be modeled as a Price/BA network.
https://en.wikipedia.org/wiki/Barab%C3%A1si%E2%80%93Albert_model
You end up with few large influencers.
Honestly, I'm not a fan...
GitHubAdd cold start follow recommendations by Gargron · Pull Request #15945 · mastodon/mastodon