Fourier Feature Networks
bmild.github.io · 827 words · saved by 2 readers
Project page for Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains.
Fourier Feature Networks --> --> Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains NeurIPS 2020 (spotlight) Matthew Tancik* UC Berkeley Pratul Srinivasan* UC Berkeley Ben Mildenhall* UC Berkeley Sara Fridovich-Keil UC Berkeley Nithin Raghavan UC Berkeley Utkarsh Singhal UC Berkeley Ravi Ramamoorthi UC San Diego Jonathan T. Barron Google Research Ren Ng UC Berkeley *denotes equal contribution Paper Code Abstract We show that passing input points through a simple Fourier feature mapping enables a multilayer perceptron (MLP) to learn high-frequency functions
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