
Jiaxiang Zhang
@ccbrainlab
Brain researcher @CompFoundry @CUBRICcardiff. Interested in #Cognition #Brain #Imaging #Neurogeneration #Computationalmodel
ID: 278198715
http://ccbrain.org 06-04-2011 20:17:25
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Missed out on ICLR Re-Align? No fear - here is a 🧵 on our new work: "Topoformer: brain-like topographic organization in Transformer language models through spatial querying and reweighting" led by the fearless Taha Binhuraib 🦉, with the inimitable Greta Tuckute 1/n


🚨BREAKING: the The Royal Society publishes "Science in the Age of AI - How AI is changing the nature and method of scientific research," and it's a must-read for everyone interested in AI & science. Important information: ➡️According to the official release, the report addresses


Tomassini et al. report that #Parkinsons disease disrupts the beta-frequency activity mediating the accumulation of evidence for decision-making, leading to inefficient processing. Alessandro Tomassini 🇺🇦 Cambridge FTD Jiaxiang Zhang Thomas Cope edin.ac/3Xxnj90



📢Job Alert! We have a 2-year postdoc position to investigate the neural mechanisms of depression, in the context of immune-mediated inflammatory diseases, using state-of-the-art brain imaging (7TfMRI-EEG) CCNi_UofGlasgow @UofGPsychNeuro UofG Sii UofG School of Health & Wellbeing jobs.ac.uk/job/DJA346/res…








"Large language models surpass human experts in predicting neuroscience results" w Xiaoliang (Ken) Luo and BrainGPT.org. LLMs integrate a noisy yet interrelated scientific literature to forecast outcomes. nature.com/articles/s4156… 1/8


Excited to share our paper in Current Biology, on a unified and parsimonious model for humans and macaque monkeys playing PAC-MAN . It was an excellent team effort with Tianming Yang 杨天明 , where we played a small part. cell.com/current-biolog…

Our team Reality Labs at Meta has made amazing progress in predicting hand pose from sEMG. Now we're releasing a huge dataset, with code and competitive benchmark models. Excited to see what you can do: github.com/facebookresear…

Excited to share our work MatchAnything: We pre-train strong universal image matching models that exhibit remarkable generalizability on unseen multi-modality matching and registration tasks. Project page: zju3dv.github.io/MatchAnything/ Huggingface Demo: huggingface.co/spaces/LittleF…

So excited to share that DeepPrep is now online in Nature Methods! 🚀 It’s 10× faster than the SOTA pipeline and more robust in handling clinical cases. We’ve just released v25.1.0 with a concise GUI and support for both Win and Linux. Give it a try! 📷 shorturl.at/0pB4H
