
merging adaptive motor control & machine learning | Prof @EPFL | 🐭@deeplabcut 🦓@cebraAI | @ELLISforEurope Scholar | @Harvard Alum | https://xitter.cf/t.co/FakcYoDAC3
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Joined February 2011
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🦓 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.
📝 doi.org/10.1038/s41586-023-0…
💻github.com/AdaptiveMotorCont…
🦓 cebra.ai/
🧵⬇️
Mackenzie Weygandt Mathis, PhD retweeted
We’re excited to announce DiG-bench, a new benchmark for discovery!
Over the last few weeks we’ve been testing frontier AI models on our novel discovery games and seeing how they score. Each game is a text-based environment, so they probe discovery capabilities in the natural domain of language models, rather than requiring additional, potentially confounding, visual understanding.
TL;DR frontier models have improved a lot over the last few months. But they are still stumped by some surprisingly simple problems, even in their native text domain.
With
@cocosci_lab (@Princeton) @MITCoCoSci (@MIT) @SchmidhuberAI (@KAUST_News) @misovalko (@Inria) @tri_dao (@PrincetonCS) @RMBattleday @zebkDotCom @FraserGreenlee @akaijsa @ClareMaguire @TimMuller1 @kubicek_ales @physicscat0x7d @SukritSumant @thoughtchannel_
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Mackenzie Weygandt Mathis, PhD retweeted
Thanks to everyone sharing in this moment!
I’m so grateful to my trainees & collaborators…
dlab.stanford.edu/group-memb…
(pic: optogenetics conference chairs, Tuscany)
Reading for all those asking:
for technical details: dlab.stanford.edu
for everyone: deisseroth.org/projections
Now accepted at #Neurips 🙌💗🔥🫶
🧠 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
📄arxiv.org/abs/2606.13260
Mackenzie Weygandt Mathis, PhD retweeted
⚠️PREPRINT ALERT⚠️
How can we better understand distributed brain activity across temporal and spatial scales?
In this collaborative project, we combined ultra-flexible electrodes with two-photon imaging to illuminate brain-wide neural dynamics.
doi.org/10.21203/rs.3.rs-102…
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Mackenzie Weygandt Mathis, PhD retweeted
🎂🥳 Wow! Happy 9 year anniversary of being published in @NatureNeuro #DeepLabCut 💜 - what an amazing adventure that first paper kicked off 🙏🏼 1.14M installations 💪
Original paper: rdcu.be/4Rep
Mackenzie Weygandt Mathis, PhD retweeted
Confused about all this talk of compositionality in neuroscience? Read our new perspective nature.com/articles/s41593-0… with authors Reidar Riveland and @pouget_alex.
Mackenzie Weygandt Mathis, PhD 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 - 💰by the Brain Initiative @NIH! Led by @celia_bqt & @sainsbury_tom
@CurrentBiology
cell.com/current-biology/ful…?
Mackenzie Weygandt Mathis, PhD retweeted
🧠 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
📄arxiv.org/abs/2606.13260
Mackenzie Weygandt Mathis, PhD retweeted
#OnThisDay in 2016, we launched the Allen Brain Observatory with the first standardized in vivo survey of physiological activity in the mouse visual cortex. Since its launch, the Observatory and its data has been critical to visual cortex research around the world.
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 - 💰by the Brain Initiative @NIH! Led by @celia_bqt & @sainsbury_tom
@CurrentBiology
cell.com/current-biology/ful…?
🧠 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
📄arxiv.org/abs/2606.13260
🥳 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 🙏
➡️ cell.com/neuron/fulltext/S08…
🥳 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 😎
We introduce *PRIMA*:🔥SOTA 2D➡️3D animal shape by @xiaoyu912huang, @TiwangCS & I!
📝 arxiv.org/abs/2606.02366
This nicely builds on top of our #SuperAnimal quadruped model (read more here: nature.com/articles/s41467-0… such that you can directly run shape inference with our pipeline!
Also, please check out our @huggingface demo: huggingface.co/spaces/MLAdap…
Thrilled to share that I’ve been promoted to Associate Professor with tenure at @EPFL! 🎉 Deeply grateful to my incredible lab, collaborators, and mentors who’ve made this journey possible. Excited for what’s ahead! 🧠✨
Nature research paper: Prefrontal to ventral tegmental area dynamics drive contingency degradation
go.nature.com/4wbtWwx
At #ICLR2026 Please check out our work #LlaVAction:
By co-first aurhors @shaokaiyeah and Haozhe Qi
TL;DR the first multi-modal LLM for action understanding and video captioning+ a new benchmark, + methods to train your MMLLMs for such tasks 🕺🏻💃🏼
💻 llavaction.epfl.ch
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