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George Cantwell

@gcant.bsky.social

Neural network interested in statistics, physics, and computing. Mostly network science. Asst prof @ Cambridge

643 Followers  |  295 Following  |  42 Posts  |  Joined: 11.11.2024  |  2.1813

Latest posts by gcant.bsky.social on Bluesky

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The perplexing β€œconnected cluster axiom” – Inverse Complexity Lab Research group on inverse problems in complex systems and network science.

I wrote a blog post about the often stated but never explained assumption that communities in graphs should always be connected.

This is inconsistent with statistical significance and null models that underlie the most widely employed methods.

skewed.de/lab/posts/co...

04.12.2025 21:10 β€” πŸ‘ 43    πŸ” 15    πŸ’¬ 3    πŸ“Œ 0

Maybe a partial answer to your question of where this idea comes from: a network is sometimes *defined* to be the largest component, e.g., the internet is the largest component of connected computers. In those cases specifically it could be sensible starting point.

05.12.2025 08:30 β€” πŸ‘ 3    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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Embedding networks with the random walk first return time distribution We propose the first return time distribution (FRTD) of a random walk as an interpretable and mathematically grounded node embedding. The FRTD assigns a probability mass function to each node, allowin...

A principled graph embedding that also appears to work well in practice: arxiv.org/abs/2512.02694

04.12.2025 10:01 β€” πŸ‘ 6    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0
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Multilayer network science: theory, methods, and applications Multilayer network science has emerged as a central framework for analysing interconnected and interdependent complex systems. Its relevance has grown substantially with the increasing availability of...

Our review on multilayer network science is out on the arXiv. Thanks to all collaborators of the AccelNet MultiNet project, great working with you all πŸ™ @alexvespi.bsky.social @ymoreno.bsky.social @lordgrilo.bsky.social @anduviera.bsky.social @baronca.bsky.social
arxiv.org/abs/2511.23371

01.12.2025 18:18 β€” πŸ‘ 16    πŸ” 9    πŸ’¬ 0    πŸ“Œ 0

Whoever created OpenReview looked at online anonymous forums and thought "yes, this is the platform to foster productive debate"

15.11.2025 08:40 β€” πŸ‘ 11    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0

Ah yes, Ramanujan's famous proof that pi^2 is rational

10.11.2025 14:13 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

Very good post. I very much agree with the overall position.

08.11.2025 11:38 β€” πŸ‘ 7    πŸ” 5    πŸ’¬ 0    πŸ“Œ 0

I suspect saying if an array is "really" a vector, or a linear transform, or a photo, or a graph, or ..., is up to us as humans

07.11.2025 07:29 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

Do you mean like: you have a (d x n) data matrix, hidden representations are, e.g., (4d x n), and the final output is say (2 x n). If so, isn't this the prototypical use case?

06.11.2025 16:19 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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Excited to introduce Vibes from Meta. Eat your slop, piggies!

30.09.2025 17:59 β€” πŸ‘ 7436    πŸ” 2680    πŸ’¬ 112    πŸ“Œ 207

Message passing for epidemiological interventions on networks with loops
https://arxiv.org/abs/2509.21596

29.09.2025 15:34 β€” πŸ‘ 6    πŸ” 5    πŸ’¬ 0    πŸ“Œ 0
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Our fall seminar series begins this Thursday, Oct. 2 (4pm UTC+1/11am EDT) with a talk by Elena Candellone. She’ll be speaking about β€œMapping extreme users through negative ties in online social interactions”, followed by a discussion on β€œthe joy of planning scientific events”.

29.09.2025 21:26 β€” πŸ‘ 10    πŸ” 5    πŸ’¬ 1    πŸ“Œ 4
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Robustness of 'small' networks Modeling how networks change under structural perturbations can yield foundational insights into network robustness, which is critical in many real-world applications. The largest connected component ...

arXiv alert! πŸ“„πŸš¨
Robustness of small networks
arxiv.org/abs/2509.23670
Great to dust off one of my favorite topics and get to collaborate with the legendary
@aliceschwarze.bsky.social and Peter Mucha

30.09.2025 05:58 β€” πŸ‘ 23    πŸ” 6    πŸ’¬ 1    πŸ“Œ 0
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Graduate Program * Complexity Science Hub Courses are offered both by CSH and by our partner universities, one of which will serve as the degree-granting entity. Students will be guided to the

#SpreadtheWord
We are looking for #PhD candidates passionate about using large-scale data analysis, quantitative models, and complexity science to study the complex interactions within #epidemiology, #OneHealth, and #publichealthsystems.
More info: csh.ac.at/education/gr...

26.09.2025 07:12 β€” πŸ‘ 4    πŸ” 3    πŸ’¬ 0    πŸ“Œ 0

The Probabilistic Systems, Information, and Inference group at the University of Cambridge is seeking applicants for funded PhD positions.

Anyone who wants to study networks/complex systems/statistical physics/inference can email me at gtc31@cam.ac.uk

18.09.2025 15:33 β€” πŸ‘ 8    πŸ” 3    πŸ’¬ 0    πŸ“Œ 0

Right, we solved directly for the stationary state, but one could also integrate for the transient. I'll look into it... thanks!

16.09.2025 15:40 β€” πŸ‘ 2    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

Oh, you have some nice calculations for the cluster expansion! But I think this reinfection counting has the same equilibrium prediction as the regular pair-approx

16.09.2025 12:47 β€” πŸ‘ 2    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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The threshold and quasi-stationary distribution for the SIS model on networks We study the Susceptible-Infectious-Susceptible (SIS) model on arbitrary networks. The well-established pair approximation treats neighboring pairs of nodes exactly while making a mean field approxima...

We found a nice way to accurately solve the SIS model. Rather than expanding in space with ever larger moment closures (pairs, triples, ...), we expand in time. No more difficult than pair-approximations yet much more accurate.
arxiv.org/abs/2509.11706

16.09.2025 11:37 β€” πŸ‘ 25    πŸ” 4    πŸ’¬ 2    πŸ“Œ 0

Strong emergence

12.09.2025 17:24 β€” πŸ‘ 52    πŸ” 8    πŸ’¬ 1    πŸ“Œ 0
Johns Hopkins University, Physics and Astronomy Job #AJO30496, Postdoctoral Fellow in Foundations of Physics, Complexity, and Emergence, Physics and Astronomy, Johns Hopkins University, Baltimore, Maryland, US

Postdoc job! I expect to have an opening at Johns Hopkins for a postdoctoral researcher working somewhere in the broad realms of physics, philosophy, and complexity. Apply at Academic Jobs Online:

academicjobsonline.org/ajo/jobs/30496

05.09.2025 17:26 β€” πŸ‘ 200    πŸ” 84    πŸ’¬ 18    πŸ“Œ 7

Not sure how many scientists here have tried Claude Code or similar command line coding assistants. I had a complicated family property tax problem that was best solved by a brute force Monte Carlo simulation approach, so I spent a few days coding up and analyzing a model with Claude Code.

12.08.2025 12:47 β€” πŸ‘ 354    πŸ” 132    πŸ’¬ 21    πŸ“Œ 45
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Applications are open for SFI's 2026 Complexity Postdoctoral Fellowships

If you’ve recently earned a Ph.D. in any scientific field and want to pursue independent, transdisciplinary research, consider applying.

Deadline: October 1, 2025
Apply here: santafe.edu/sfifellowship

28.07.2025 17:50 β€” πŸ‘ 66    πŸ” 69    πŸ’¬ 0    πŸ“Œ 3
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beautiful location for statphys

15.07.2025 14:14 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
Eric De Giuli: Noise equals endogenous control
YouTube video by Biocontrol Seminars Eric De Giuli: Noise equals endogenous control

My talk from
@bioctrl.bsky.social
about the physical origin of agency is uploaded here:
youtube.com/watch?v=YY21...
TLDR: noise equals control. Nature is constantly sampling control trajectories via noise

09.07.2025 19:27 β€” πŸ‘ 2    πŸ” 1    πŸ’¬ 1    πŸ“Œ 0
sign for "Probabilistic Systems, Information and Inference lab"

sign for "Probabilistic Systems, Information and Inference lab"

New group name! We are now the "probabilistic systems, information and inference" aka Ψ²

08.07.2025 12:53 β€” πŸ‘ 5    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

collaboration with friends @oxfordmathematics.bsky.social Erik Hormann and @lambiotte.bsky.social

12.06.2025 14:12 β€” πŸ‘ 2    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0
Approximation for return time distributions of random walks on sparse networks We propose an approximation for the first return time distribution of random walks on undirected networks. We combine a message-passing solution with a mean-field approximation to account for the shor...

The Kac formula says the average return time for a random walker is a wonderfully simple combination of global and local structure: 2m/k_i. Inspired by this result we characterize the full distribution in a similar manner. doi.org/10.1103/Phys...

12.06.2025 14:07 β€” πŸ‘ 2    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
Approximation for return time distributions of random walks on sparse networks We propose an approximation for the first return time distribution of random walks on undirected networks. We combine a message-passing solution with a mean-field approximation to account for the shor...

Approximation for return time distributions of random walks on sparse networks link.aps.org/doi/10.1103/...

12.06.2025 07:09 β€” πŸ‘ 5    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0
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The quiet before the storm.

Good morning #NetSci2025

02.06.2025 04:56 β€” πŸ‘ 27    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0
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A reader of Free Agents sent me this lovely poem by Jared Anderson... 😊

19.05.2025 09:08 β€” πŸ‘ 56    πŸ” 12    πŸ’¬ 4    πŸ“Œ 1

@gcant is following 20 prominent accounts