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Brandon Zhao retweeted
Check out this work led by my student Brandon Zhao (@joiedeposter), with @pratul, @dorverbin, @jon_barron & Y. Wang! We use trainable pyramids to solve PDEs more accurately. I even got to learn a little about PDEs along the way - handy now that they seem to be all over the news!
Introducing beignet, a new neural field architecture! beignet uses a multiresolution fourier frequency pyramid to achieve faster convergence and higher precision when solving PDEs and finding singularities. Teaser: here is beignet at work fitting an image (super fast)!
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Brandon Zhao retweeted
Really cool work by @joiedeposter and our friends at @GoogleDeepMind on a new physics-informed neural field architecture
Introducing beignet, a new neural field architecture! beignet uses a multiresolution fourier frequency pyramid to achieve faster convergence and higher precision when solving PDEs and finding singularities. Teaser: here is beignet at work fitting an image (super fast)!
Brandon Zhao retweeted
quickly! digest Brandon's paper now before he and argon solve navier stokes sometime late next week
Introducing beignet, a new neural field architecture! beignet uses a multiresolution fourier frequency pyramid to achieve faster convergence and higher precision when solving PDEs and finding singularities. Teaser: here is beignet at work fitting an image (super fast)!
Check out the paper here! arxiv.org/abs/2605.24278 Work done in collaboration w/ Yixuan Wang, @jon_barron, @klbouman, @dorverbin, @_pratul_
Recent results on unstable fluid singularities point toward harder open questions, including unforced Navier–Stokes (e.g. arxiv.org/abs/2509.14185). Burgers' is a much simpler PDE, but we think beignet might be an important building block towards something bigger!
Introducing beignet, a new neural field architecture! beignet uses a multiresolution fourier frequency pyramid to achieve faster convergence and higher precision when solving PDEs and finding singularities. Teaser: here is beignet at work fitting an image (super fast)!
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