Shakedown Social

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Andrei A. Klishinre-<a href="https://fediscience.org/tags/introduction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#introduction</a> Hi Fediscience! I am an Assistant Professor of Mechanical Engineering at University of Hawaiʻi at Mānoa (Honolulu). I got here starting from Physics training with many scientific detours into data-driven models, complex systems, nanomaterial self-assembly, human learning of complex networks, naval ships, and design problems. I grew up in Belarus and have *opinions* on that region of the world. I've been on Fediverse since late 2022 when *something* happened to our previous cybersocial infrastructure, but the previous server I was on is sunsetting. Please come say hi and recommend cool people to follow here. I have a blog with longer thoughts on science-adjacent topics. <a href="https://www.aklishin.science/blog/" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://www.aklishin.science/blog/</a> <a href="https://fediscience.org/tags/ComplexSystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComplexSystems</a> <a href="https://fediscience.org/tags/NetworkScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NetworkScience</a> <a href="https://fediscience.org/tags/DataScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DataScience</a> <a href="https://fediscience.org/tags/DynamicalSystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DynamicalSystems</a> <a href="https://fediscience.org/tags/CollectiveBehavior" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#CollectiveBehavior</a> <a href="https://fediscience.org/tags/StatisticalPhysics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#StatisticalPhysics</a>

DurstewitzLabCan time series (TS) <a href="https://mathstodon.xyz/tags/FoundationModels" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#FoundationModels</a> (FM) like Chronos zero-shot generalize to unseen <a href="https://mathstodon.xyz/tags/DynamicalSystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DynamicalSystems</a> (DS)? <a href="https://mathstodon.xyz/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#AI</a>No, they cannot!But *DynaMix* can, the first TS/DS foundation model based on principles of DS reconstruction, capturing the long-term evolution of out-of-domain DS: <a href="https://arxiv.org/pdf/2505.13192v1" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://arxiv.org/pdf/2505.13192v1</a>Unlike TS foundation models, DynaMix exhibits <a href="https://mathstodon.xyz/tags/ZeroShotLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ZeroShotLearning</a> of long-term stats of unseen DS, incl. attractor geometry & power spectrum, w/o *any* re-training, just from a context signal. It does so with only 0.1% of the parameters of Chronos & 10x faster inference times than the closest competitor.It often even outperforms TS FMs on forecasting diverse empirical time series, like weather, traffic, or medical data, typically used to train TS FMs. This is surprising, cos DynaMix’ training corpus consists *solely* of simulated limit cycles & chaotic systems, no empirical data at all!And no, it’s neither based on Transformers nor Mamba – it’s a new type of mixture-of-experts architecture based on the recently introduced AL-RNN (<a href="https://proceedings.neurips.cc/paper_files/paper/2024/file/40cf27290cc2bd98a428b567ba25075c-Paper-Conference.pdf" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://proceedings.neurips.cc/paper_files/paper/2024/file/40cf27290cc2bd98a428b567ba25075c-Paper-Conference.pdf</a>), specifically trained for DS reconstruction.Remarkably, DynaMix not only generalizes zero-shot to novel DS, but it can even generalize to new initial conditions and regions of state space not covered by the in-context information.We dive a bit into the reasons why current time series FMs not trained for DS reconstruction fail, and conclude that a DS perspective on time series forecasting & models may help to advance the <a href="https://mathstodon.xyz/tags/TimeSeriesAnalysis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#TimeSeriesAnalysis</a> field.

Alexander HölkenMy commentary on our 2023 LIDA paper just got published! In it, I explore the idea that the behavioral and cognitive dispositions our original paper was concerned with may be understood as topological features of cognitive subsystems: <a href="https://journals.sagepub.com/doi/10.1177/00368504241245812" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://journals.sagepub.com/doi/10.1177/00368504241245812</a><a href="https://discuss.systems/tags/CogSci" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#CogSci</a> <a href="https://discuss.systems/tags/Dispositions" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Dispositions</a> <a href="https://discuss.systems/tags/DynamicalSystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DynamicalSystems</a> <a href="https://discuss.systems/tags/LIDA" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#LIDA</a>

Yohan John 🤖🧠" we provide neural evidence that energy landscapes predict decision consistency, which reflects decision confidence."<a href="https://www.nature.com/articles/s41593-023-01445-x" rel="nofollow noopener noreferrer" target="_blank">https://www.nature.com/articles/s41593-023-01445-x</a><a href="https://fediscience.org/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://fediscience.org/tags/DynamicalSystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DynamicalSystems</a>

Non-Euclidean DreamerTaught my code to write powers. Am I slowly reinventing LaTeX? 😅<a href="https://mathstodon.xyz/tags/codeart" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#codeart</a> <a href="https://mathstodon.xyz/tags/mastoart" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#mastoart</a> <a href="https://mathstodon.xyz/tags/fractal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#fractal</a> <a href="https://mathstodon.xyz/tags/dynamicalsystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#dynamicalsystems</a>

Non-Euclidean DreamerNew Full Video: <a href="https://youtu.be/O6Un816f51c" rel="nofollow noopener noreferrer" target="_blank">https://youtu.be/O6Un816f51c</a>Teaser Pic: <a href="https://mathstodon.xyz/tags/fractal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#fractal</a> <a href="https://mathstodon.xyz/tags/mastoart" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#mastoart</a> <a href="https://mathstodon.xyz/tags/codeart" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#codeart</a> <a href="https://mathstodon.xyz/tags/dynamicalsystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#dynamicalsystems</a>

myrmepropagandistWhat is the connection between fractal geometry and systems at a critical point undergoing phase transition? This is one of the more useful ideas that has emerged from the study of dynamical systems, but often it's buried too deep into the study of modeling for most people to encounter it-- then it gets explained badly in pop-science books. At last here is a video that will set you right:<a href="https://www.youtube.com/watch?v=vwLb3XlPCB4" rel="nofollow noopener noreferrer" target="_blank">https://www.youtube.com/watch?v=vwLb3XlPCB4</a><a href="https://sauropods.win/tags/dynamicalsystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#dynamicalsystems</a> <a href="https://sauropods.win/tags/mathematics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#mathematics</a> <a href="https://sauropods.win/tags/videos" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#videos</a> <a href="https://sauropods.win/tags/phasechange" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#phasechange</a> <a href="https://sauropods.win/tags/simulations" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#simulations</a> <a href="https://sauropods.win/tags/chaos" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#chaos</a>

Dominic BoutetJust moved to neuromatch.social, so here it goes (again), <a href="https://neuromatch.social/tags/introduction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#introduction</a> :Hi everyone, I'm a last year undergrad in <a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> & <a href="https://neuromatch.social/tags/ComputerScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputerScience</a> at McGill. I'm doing <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputationalNeuroscience</a> research in the Baillet Lab at The Neuro (MNI), focusing on whole-brain dynamical models of coupled neural masses calibrated to <a href="https://neuromatch.social/tags/MEG" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MEG</a> <a href="https://neuromatch.social/tags/Neuroimaging" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroimaging</a> data (more details @ <a href="https://neurolife77.github.io/" rel="nofollow noopener noreferrer" target="_blank">https://neurolife77.github.io/</a> if anyone is curious). I am also the VP of the <a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLearning</a> committee at PharmaHacks, a hackathon that blends <a href="https://neuromatch.social/tags/Biology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Biology</a> & <a href="https://neuromatch.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DataScience</a> with a focus on <a href="https://neuromatch.social/tags/Pharma" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Pharma</a>. @neuroscience <a href="https://neuromatch.social/tags/neurodon" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#neurodon</a>------------------------ Bonus ------------------------Since I have the space to put it in the same post now, thanks to the freedom in post length from this new server, here's a bonus:I regularly share links to preprints that catch my attention and tag them with: <a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a>I started doing this because I thought that the arxiv bots on mastodon were not super efficient, but after doing it for about a month I'd say it's also a good way to keep some form of history of my nightly exploration of the literature in my fields of interest. I usually share stuff about <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputationalNeuroscience</a>, <a href="https://neuromatch.social/tags/Neuroimaging" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroimaging</a>, <a href="https://neuromatch.social/tags/DynamicalSystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DynamicalSystems</a>, <a href="https://neuromatch.social/tags/MachineLeaning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLeaning</a>, <a href="https://neuromatch.social/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ArtificialIntelligence</a>, etc. Disclaimer: I usually only read the abstract or skim through them at the time of posting. Disclaimer 2: I am definitely not consistent.

Paul Marrow 🇪🇺<a href="https://ecoevo.social/tags/ecoevo" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ecoevo</a> folks <a href="https://ecoevo.social/tags/introductions" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#introductions</a> <a href="https://ecoevo.social/tags/introduction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#introduction</a>. I am a former <a href="https://ecoevo.social/tags/evolutionary" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#evolutionary</a> <a href="https://ecoevo.social/tags/ecologist" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ecologist</a>. DPhil <a href="https://ecoevo.social/tags/UYorkUK" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#UYorkUK</a> <a href="https://ecoevo.social/tags/evolutionarydynamics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#evolutionarydynamics</a> (<a href="https://ecoevo.social/tags/adaptivedynamics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#adaptivedynamics</a>) <a href="https://ecoevo.social/tags/populationdynamics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#populationdynamics</a> <a href="https://ecoevo.social/tags/gametheory" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#gametheory</a> <a href="https://ecoevo.social/tags/dynamicalsystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#dynamicalsystems</a> <a href="https://ecoevo.social/tags/evolutionarystablestrategies" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#evolutionarystablestrategies</a> <a href="https://ecoevo.social/tags/ESS" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ESS</a>. Postdoc <a href="https://ecoevo.social/tags/ULeiden" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ULeiden</a> continued this. Postdoc <a href="https://ecoevo.social/tags/UCambridge" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#UCambridge</a> <a href="https://ecoevo.social/tags/lifehistoryevolution" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#lifehistoryevolution</a> <a href="https://ecoevo.social/tags/soaysheepproject" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#soaysheepproject</a> <a href="https://ecoevo.social/tags/modelling" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#modelling</a> <a href="https://ecoevo.social/tags/reproductivestrategies" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#reproductivestrategies</a> <a href="https://ecoevo.social/tags/dynamicprogramming" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#dynamicprogramming</a> <a href="https://ecoevo.social/tags/fielddata" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#fielddata</a> Where did this lead to? Recruitment into business for <a href="https://ecoevo.social/tags/bioinspiredcomputing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#bioinspiredcomputing</a>

Jitse NiesenHello everybody, here is my <a href="https://mathstodon.xyz/tags/introduction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#introduction</a>.I am Jitse (he/him), originally from the Netherlands but working in the School of Mathematics at the University of <a href="https://mathstodon.xyz/tags/Leeds" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Leeds</a>, UK for 10+ years. Research interests: <a href="https://mathstodon.xyz/tags/NumericalAnalysis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NumericalAnalysis</a> and <a href="https://mathstodon.xyz/tags/DynamicalSystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DynamicalSystems</a>. Lately working on Fourier extension, geometric numerical integration and applications in particle methods in plasma physics and compartments models in chemistry. I contribute to <a href="https://mathstodon.xyz/tags/Spyder" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Spyder</a>, an open=source IDE for Python geared towards scientists.

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