@wellingmax
Could the “guy who worked on Alphafold” saying “This paper sure saved our ass on that Nobel prize” come forward please? Maybe a citation would have been nice 😪. https://t.co/UXegfxZHz2
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Could the “guy who worked on Alphafold” saying “This paper sure saved our ass on that Nobel prize” come forward please? Maybe a citation would have been nice 😪. https://t.co/UXegfxZHz2
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"full_text": "CNNs (@ylecun, @Yoshua_Bengio) led to Spherical CNNs (@TacoCohen, @mario1geiger, @jonkhler, @wellingmax), and eventually to the SE(3) Transformer (@FabianFuchsML, @danielewworrall, Volker Fischer, @wellingmax).\n\nSE(3) is the special euclidean group, consisting of rigid translations and proper rotations in 3 dimensions—meaning it inherently respects the structure of euclidean space. An architecture with this property is indispensable for moving from fixed grids to freely moving cells.\n\nThe power of Equivariant transformers can be seen through its use in AlphaFold, which outputs the 3D coordinates of all heavy atoms for a given protein using the primary amino acid sequence and aligned sequences of homologues as inputs (@GoogleDeepMind, John Jumper, @demishassabis)\nAlphaFold recently won the Nobel Prize in Chemistry for its groundbreaking advance in protein structure prediction.\n\nThe particular architecture I currently use is the Equiformer (@yilunliao, @tesssmidt), which builds on all of these ideas.",
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