rulands.bsky.social
Professor at LMU Munich. Theoretical physics, biophysics, artificial intelligence
12 posts
308 followers
180 following
Regular Contributor
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The same model also explains the much faster transition in mouse. Apart from genetic oscillators the transcriptional hourglass is a second paradigm of how cells determine time.
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Our work demonstrates emergence in the training of deep neural networks, which impacts the achievable performance of deep neural networks. By Pascal de Jong and Felix Meigel.
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We derive a theory from first principles that predicts that the homogeneous state of deep neural networks is unstable in a way that leads to the emergence of periodic channel structures.
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We show that this behaviour relates to a PRC2 driven phenomenon that resembles wetting of fluids. Check out the preprint to find out more. By Aida Hashtroud with Wolf Reik, @vonmeyennlab.bsky.social , @steglelab.bsky.social Mark Jan Bonder
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Thanks, could you add me, please?
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He's been throwing things from left to right 10^23 times...