Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

18 June 2020

Papers citing "Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains"

8 / 1,458 papers shown

Title
Implicit Neural Representations with Periodic Activation Functions Vincent Sitzmann Julien N. P. Martel Alexander W. Bergman David B. Lindell Gordon Wetzstein AI4TS 6 2,472 0 17 Jun 2020
70 years of machine learning in geoscience in review Jesper Sören Dramsch VLM AI4CE 24 160 0 16 Jun 2020
SALD: Sign Agnostic Learning with Derivatives Matan Atzmon Y. Lipman 11 143 0 09 Jun 2020
Neural Additive Models: Interpretable Machine Learning with Neural Nets Rishabh Agarwal Levi Melnick Nicholas Frosst Xuezhou Zhang Ben Lengerich R. Caruana Geoffrey E. Hinton 27 405 0 29 Apr 2020
Local Implicit Grid Representations for 3D Scenes C. Jiang Avneesh Sud A. Makadia Jingwei Huang Matthias Nießner Thomas Funkhouser 3DPC 214 558 0 19 Mar 2020
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis B. Mildenhall Pratul P. Srinivasan Matthew Tancik Jonathan T. Barron R. Ramamoorthi Ren Ng 8 2,605 0 19 Mar 2020
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks Blake Bordelon Abdulkadir Canatar C. Pehlevan 131 200 0 07 Feb 2020
NASA: Neural Articulated Shape Approximation Boyang Deng J. P. Lewis Timothy Jeruzalski Gerard Pons-Moll Geoffrey E. Hinton Mohammad Norouzi Andrea Tagliasacchi 14 211 0 06 Dec 2019