{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T15:48:56Z","timestamp":1778255336287,"version":"3.51.4"},"reference-count":24,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,4,6]],"date-time":"2025-04-06T00:00:00Z","timestamp":1743897600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,4,6]],"date-time":"2025-04-06T00:00:00Z","timestamp":1743897600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004489","name":"Mitacs","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004489","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,4,6]]},"DOI":"10.1109\/icassp49660.2025.10890471","type":"proceedings-article","created":{"date-parts":[[2025,3,12]],"date-time":"2025-03-12T17:15:02Z","timestamp":1741799702000},"page":"1-5","source":"Crossref","is-referenced-by-count":4,"title":["Implicit Neural Representations with Fourier Kolmogorov-Arnold Networks"],"prefix":"10.1109","author":[{"given":"Ali","family":"Mehrabian","sequence":"first","affiliation":[{"name":"The University of British Columbia,Department of Electrical and Computer Engineering,Vancouver,Canada"}]},{"given":"Parsa Mojarad","family":"Adi","sequence":"additional","affiliation":[{"name":"Shahid Beheshti University,Institute of Medical Science and Technology,Tehran,Iran"}]},{"given":"Moein","family":"Heidari","sequence":"additional","affiliation":[{"name":"The University of British Columbia,School of Biomedical Engineering,Vancouver,Canada"}]},{"given":"Ilker","family":"Hacihaliloglu","sequence":"additional","affiliation":[{"name":"The University of British Columbia,Department of Radiology,Vancouver,Canada"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_24"},{"key":"ref2","article-title":"Implicit neural representations with periodic activation functions","volume-title":"Proc. Conf. Neural Inf. Process. Syst. (NeurIPS), Virtual","author":"Sitzmann"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00025"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02455"},{"key":"ref5","article-title":"On the spectral bias of neural networks","volume-title":"Proc. Int\u2019l Conf. Machine Learning (ICML)","author":"Rahaman"},{"key":"ref6","article-title":"Understanding training and generalization in deep learning by Fourier analysis","author":"Xu","year":"2018"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW63382.2024.00288"},{"key":"ref8","article-title":"A closer look at memorization in deep networks","volume-title":"Proc. Int\u2019l Conf. Machine Learning (ICML)","author":"Arpit"},{"key":"ref9","article-title":"Fourier features let networks learn high frequency functions in low dimensional domains","volume-title":"Proc. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Tancik"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20050-2_19"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01775"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19827-4_9"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00262"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00595"},{"key":"ref15","article-title":"Single-layer learnable activation for implicit neural representation (SL2A-INR)","author":"Heidari","year":"2024"},{"key":"ref16","article-title":"KAN: Kolmogorov-Arnold networks","author":"Liu","year":"2024"},{"key":"ref17","article-title":"FourierKAN-GCF: Fourier Kolmogorov-Arnold network\u2013An effective and efficient feature transformation for graph collaborative filtering","author":"Xu","year":"2024"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00133"},{"issue":"5","key":"ref19","first-page":"953","article-title":"On the representation of continuous functions of many variables by superposition of continuous functions of one variable and addition","volume-title":"Doklady Akademii Nauk","volume":"114","author":"Kolmogorov","year":"1957"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-81897-4_4"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2024.3375816"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICC51166.2024.10622400"},{"key":"ref23","article-title":"PyTorch: An imperative style, high-performance deep learning library","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NeurIPS)","author":"Paszke"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1406.3269"}],"event":{"name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","location":"Hyderabad, India","start":{"date-parts":[[2025,4,6]]},"end":{"date-parts":[[2025,4,11]]}},"container-title":["ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10887540\/10887541\/10890471.pdf?arnumber=10890471","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T05:23:04Z","timestamp":1774416184000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10890471\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,6]]},"references-count":24,"URL":"https:\/\/doi.org\/10.1109\/icassp49660.2025.10890471","relation":{},"subject":[],"published":{"date-parts":[[2025,4,6]]}}}