George Cantwell

@gcant.bsky.social

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

Also shows there is new physics to discover: a learned equation was more accurate than one derived by standard argument, so a better approximation *exists*. Now we just need to find it from first principles!

Joe Bacchus George@joebacbac.bsky.social · last wk.

Neural networks can supposedly solve a Millennium Prize problem, but they still can't colour graphs... I am pleased to share my first preprint on combinatorial optimisation with @gcant.bsky.social. Read more: arxiv.org/pdf/2609.07456

At the end of the term I asked my college creative wriing students to submit anonymous thoughts on AI. No real surprises: Mood ranges from resignation to despair, capitulation from embittered erosion of standards to total, feelings of betrayal from deep to furious. 1/

Interested in network science, evolutionary biology, and animal behavior? I am seeking a PhD student to join the Quantitative Network Science group at the Department of Mathematical Modeling and Machine Learning of the University of Zurich. Info and application here: jobs.uzh.ch/job-vacancie...

UZH: PhD in Network Science: Modeling of Animal Networks

We are seeking a highly motivated PhD student to join our Quantitative Network Science research group at the Department of Mathematical Modeling and Machine Learning at the University of Zurich. Wild ...

jobs.uzh.ch

We wrote a perspective piece on future directions & challenges for stochastic thermodynamics. Great collaboration with Jan Korbel, Sarah Loos, Gonzalo Manzano, Rosalba Garcia-Millan, Olga Movilla Miangolarra, Edgar Roldan arxiv.org/abs/2604.26601

Quo vadis, stochastic thermodynamics?

Stochastic thermodynamics is a framework for describing non-equilibrium processes at the level of fluctuating trajectories, where the state of a system evolves as a stochastic time series,...

arxiv.org

Next week, my course on Networks and Complexity is starting again, which is always taught online. We have some space left for international students. Lectures will be on mondays and thursdays 16:00-18:00 CEST. Starting 9th. 24 Lectures total. More info in the reply.

Journal publishing is bad now, but …this year is the 40th anniversary of my first published paper and the 43rd anniversary of it being accepted for publication.

Can't get over the fact that in the ML literature the act of *sampling* from an inferred model is now called “inference.” We really are in the worst timeline.

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 “Mapping extreme users through negative ties in online social interactions”, followed by a discussion on “the joy of planning scientific events”.

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