{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/implicit-neural-representations-with-periodic","title":"Implicit Neural Representations with Periodic Activation Functions","arxiv_id":"2006.09661","date":"2020-06-17","proceeding":"NeurIPS 2020 12","authors":["Vincent Sitzmann","Julien N. P. Martel","Alexander W. Bergman","David B. Lindell","Gordon Wetzstein"],"abstract":"Implicitly defined, continuous, differentiable signal representations parameterized by neural networks have emerged as a powerful paradigm, offering many possible benefits over conventional representations. 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