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Merging artificial and natural intelligence to study adaptive mechanisms | CV, ML, Neuro | PI: @trackingactions
@EPFL π¨π
Joined June 2017
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π¦π¦π¦ #CEBRA is out πππ
Check out the @Nature paper β¬οΈ & the gorgeous code & resources built by current members @stes_io @BenquetCelia @TrackingActions
@EPFL_en @epflSV
π how to use: cebra.ai/docs/usage.html
π» install: cebra.ai/docs/installation.hβ¦
πnature.com/articles/s41586-0β¦
π¦ Self-supervised multimodal ML is promising the next AI breakthrough - in our new work published in @Nature, we debut @CEBRAai: for self-supervised hypothesis- and discovery-driven science.
π doi.org/10.1038/s41586-023-0β¦
π»github.com/AdaptiveMotorContβ¦
π¦ cebra.ai/
π§΅β¬οΈ
M- Lab of Adaptive Intelligence @EPFL retweeted
ππ₯³ Wow! Happy 9 year anniversary of being published in @NatureNeuro #DeepLabCut π - what an amazing adventure that first paper kicked off ππΌ 1.14M installations πͺ
Original paper: rdcu.be/4Rep
M- Lab of Adaptive Intelligence @EPFL retweeted
Mice perform active sensing to acquire visual info: check out our collaborative effort, which is our 1st in motor+vision!
Great to work with @AToliasLab Xaq and Cris - π°by the Brain Initiative @NIH! Led by @celia_bqt & @sainsbury_tom
@CurrentBiology
cell.com/current-biology/ful�
M- Lab of Adaptive Intelligence @EPFL retweeted
π§ Can we recover the equations governing a system directly from noisy, high-dimensional observations?
#DYSCO, by Paolo Muratore, is a first step: it learns latent spaces that capture the underlying dynamics & enables recovery of governing equations
πarxiv.org/abs/2606.13260
M- Lab of Adaptive Intelligence @EPFL retweeted
Online now: The Simons Collaboration on Ecological Neuroscience: Studying how the brain interacts with the world dlvr.it/TSyBZX
M- Lab of Adaptive Intelligence @EPFL retweeted
π₯³ Excited that our Perspective about our new @SimonsFdn Collaboration: SCENE is out in @NeuroCellPress !
A great team effort across all the PIs, championed by @lengyel_m and @JP__NOEL π
β‘οΈ cell.com/neuron/fulltext/S08β¦
Interested in how we estimate 3D poses for humans and animals using flow matching?
Come check out our work, #FMPose3D, at CVPR 2026!
Today at the CV4Animals Workshop poster session:
11:30 a.m.β12:30 p.m., ExHall A
Looking forward to seeing you there! π
M- Lab of Adaptive Intelligence @EPFL retweeted
π₯³ New work from my lab (@MLabofAI) just dropped on @arxiv! Measuring the shape of an animal can be highly useful for biomedical applications and for avatars π
We introduce *PRIMA*:π₯SOTA 2Dβ‘οΈ3D animal shape by @xiaoyu912huang, @TiwangCS & I!
π arxiv.org/abs/2606.02366
M- Lab of Adaptive Intelligence @EPFL retweeted
π¨ β¨ New 3D pose estimation method from @mwmathislab! #FMPose3D allows for monocular (i.e. single camera) 2D β‘οΈ 3D π₯
Led by @TiwangCS & w/@xiaoyu912huang #FMPose3D is SOTA on human & animal 3D benchmarks, & will be integrated into @DeepLabCut β¬οΈπ
π arxiv.org/abs/2602.05755
M- Lab of Adaptive Intelligence @EPFL retweeted
π¨ β¨ New 3D pose estimation method from @mwmathislab! #FMPose3D allows for monocular (i.e. single camera) 2D β‘οΈ 3D π₯
Led by @TiwangCS & w/@xiaoyu912huang #FMPose3D is SOTA on human & animal 3D benchmarks, & will be integrated into @DeepLabCut β¬οΈπ
π arxiv.org/abs/2602.05755
M- Lab of Adaptive Intelligence @EPFL retweeted
π Finding clinical trials & knowing which are useful is an overwhelming task, even if you know where to start!
I worked on a simple @Gradio app for parsing clinical trials+ adding a #DeepSeek model to rank trials + user Q&A. I hope its useful to many:
clinicaltrialmatcher.org
M- Lab of Adaptive Intelligence @EPFL retweeted
π» reID of unmarked Grizzly's in Alaskan wilderness from single images is a daunting task, but in our new work out in @CurrentBiology that is exactly what Beth Rosenberg & Mu Zhou & @TrackingPlumes! π₯ Check out the work - many years in the making...
sciencedirect.com/science/arβ¦
M- Lab of Adaptive Intelligence @EPFL retweeted
π₯πΎ massive congratulations to @shaokaiyeah and Haozhe Qi for #LLaVAction to be accepted to #ICLR2026!
TL;DR the first MMLLM for action understanding, + a new benchmark, + methods to train your MMLLMs for such tasks πΊπ»ππΌ
π» llavaction.epfl.ch/
π arxiv.org/abs/2503.18712
M- Lab of Adaptive Intelligence @EPFL retweeted
π¨ Looking for a primer on the latest advances in joint neural-behavioral modeling?
π€© Check out our new Nature Reviews Neuroscience piece! It was really an honor to write this π«Ά
nature.com/articles/s41583-0β¦
Nature Neuroscience
Leveraging insights from neuroscience to build adaptive artificial intelligence
nature.com/articles/s41593-0β¦
M- Lab of Adaptive Intelligence @EPFL retweeted
π How can we use new neuroscience insights to build *adaptive* AI agents and leverage the many foundation models ( which are much like different brain areas)?
Check out my pitch in @NatureNeuro in the Jan 2026 issue π β¬οΈ
nature.com/articles/s41593-0β¦
#AIagents #neuroscience #AGI
M- Lab of Adaptive Intelligence @EPFL retweeted
Delighted to have my perspective on how we can leverage the latest insights from neuroscience to build adaptive AI agents out in @NatureNeuro π€π
π nature.com/articles/s41593-0β¦
M- Lab of Adaptive Intelligence @EPFL retweeted
Interested in the latest advances in neuroscience (neural dynamics and internal models) and how they can be leveraged to build smarter, adaptive AI?
β‘οΈ My first real solo piece π€π«Ά @NatureNeuro
rdcu.be/eWVmA
M- Lab of Adaptive Intelligence @EPFL retweeted
The 2025 lab swag / holiday kit! π«π·π§ββοΈ- happy holidays everyone!
M- Lab of Adaptive Intelligence @EPFL retweeted
The Swiss Laboratory Animal Science Association awarded on Wednesday its 2025 Prize to neuroscientist Mackenzie Mathis, Professor at EPFL, βfor her outstanding contribution to the refinement of animal research.βΒ
go.epfl.ch/6689f9
M- Lab of Adaptive Intelligence @EPFL retweeted
Joint modelling of brain and behaviour dynamics with artificial intelligence β a Review by Mackenzie Weygandt Mathis & Alexander Mathis
@TrackingActions @TrackingPlumes
nature.com/articles/s41583-0β¦