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Introducing "Automatic Integration (AutoInt)": a new method using neural networks to learn closed-form solutions to integrals.
http://www.computationalimaging.org/publications/automatic-integration/ …
We demonstrate AutoInt for neural volume rendering, achieving >10x speedup compared to NeRF! (1/n)
@jnpmartel @GordonWetzsteinpic.twitter.com/OOgPzN3pdB
Really interesting! Also interesting connections to our neural operator for PDEs since solution operators of PDEs are integral operators. For linear PDE, we have Green's function. For non-linear PDE: composition of linear operators: our neural operatorhttps://twitter.com/AnimaAnandkumar/status/1319055677260611586?s=20 …
David and I, have been impressed by Neural Fourier Operators: this line of work is very inspiring. AutoInt is in the continuity of our SIRENs (NeurIPS'20) where we also solve PDEs with "implicit representations" w/o generalization yet (contrary to NFO)https://twitter.com/vincesitzmann/status/1273409377395859456 …
Thanks @jnpmartel Indeed the two lines of work have nice connections. Incorporating AutoInt framework for inverse problems using neural operator would be one interesting application. @ZongyiLiCaltech @kazizzad
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