{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T06:36:11Z","timestamp":1782455771671,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":20,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,8]],"date-time":"2024-10-08T00:00:00Z","timestamp":1728345600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,8]]},"DOI":"10.1145\/3703412.3703427","type":"proceedings-article","created":{"date-parts":[[2025,3,5]],"date-time":"2025-03-05T11:49:51Z","timestamp":1741175391000},"page":"1-10","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["KANICE: Kolmogorov-Arnold Networks with Interactive Convolutional Elements"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8833-2274","authenticated-orcid":false,"given":"Md Meftahul","family":"Ferdaus","sequence":"first","affiliation":[{"name":"University of New Orleans, New Orleans, US"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0932-2009","authenticated-orcid":false,"given":"Mahdi","family":"Abdelguerfi","sequence":"additional","affiliation":[{"name":"University of New Orleans, New Orleans, US"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-3699-6762","authenticated-orcid":false,"given":"Elias","family":"Ioup","sequence":"additional","affiliation":[{"name":"Center for Geospatial Sciences, Naval Research Laboratory, Stennis Space Center, Mississippi, US"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5237-3496","authenticated-orcid":false,"given":"David","family":"Dobson","sequence":"additional","affiliation":[{"name":"Center for Geospatial Sciences, Naval Research Laboratory, Stennis Space Center, Mississippi, US"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2925-8856","authenticated-orcid":false,"given":"Kendall N.","family":"Niles","sequence":"additional","affiliation":[{"name":"US Army Corps of Engineers, Engineer Research and Development Center, Vicksburg, US"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2782-4092","authenticated-orcid":false,"given":"Ken","family":"Pathak","sequence":"additional","affiliation":[{"name":"US Army Corps of Engineers, Engineer Research and Development Center, Vicksburg, US"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4038-119X","authenticated-orcid":false,"given":"Steven","family":"Sloan","sequence":"additional","affiliation":[{"name":"US Army Corps of Engineers, Engineer Research and Development Center, Vicksburg, US"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,3,5]]},"reference":[{"key":"e_1_3_3_1_2_2","unstructured":"Alexander\u00a0Dylan Bodner Antonio\u00a0Santiago Tepsich Jack\u00a0Natan Spolski and Santiago Pourteau. 2024. Convolutional Kolmogorov-Arnold Networks. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2406.13155 (2024)."},{"key":"e_1_3_3_1_3_2","unstructured":"Cristian J. Vaca-Rubio Luis Blanco Roberto Pereira and Marius Caus. 2024. Kolmogorov-Arnold Networks (KANs) for Time Series Analysis. (2024)."},{"key":"e_1_3_3_1_4_2","unstructured":"Jane Doe and Michael Brown. 2022. Adaptive Architectures in Deep Learning for Visual Recognition. IEEE Transactions on Neural Networks and Learning Systems 33 2 (2022) 123\u2013145."},{"key":"e_1_3_3_1_5_2","unstructured":"Emadeldeen Eldele Mohamed Ragab Zhenghua Chen Min Wu and Xiaoli Li. 2024. Tslanet: Rethinking transformers for time series representation learning. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2404.08472 (2024)."},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"crossref","unstructured":"Federico Girosi and Tomaso Poggio. 1989. Representation Properties of Networks: Kolmogorov\u2019s Theorem Is Irrelevant. Neural Computation 1 4 (12 1989) 465\u2013469.","DOI":"10.1162\/neco.1989.1.4.465"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"publisher","unstructured":"Aysu Ismayilova and Vugar Ismailov. 2023. On the Kolmogorov neural networks. ArXiv abs\/2311.00049 (2023). 10.48550\/arXiv.2311.00049","DOI":"10.48550\/arXiv.2311.00049"},{"key":"e_1_3_3_1_8_2","unstructured":"D. Konstantinidis Ilias Papastratis K. Dimitropoulos and P. Daras. 2022. Multi-Manifold Attention for Vision Transformers. ArXiv abs\/2207.08569 (2022)."},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"crossref","unstructured":"V\u011bra K\u016frkov\u00e1. 1991. Kolmogorov\u2019s Theorem Is Relevant. Neural Computation 3 4 (12 1991) 617\u2013622.","DOI":"10.1162\/neco.1991.3.4.617"},{"key":"e_1_3_3_1_10_2","unstructured":"Ziming Liu Yixuan Wang Sachin Vaidya Fabian Ruehle James Halverson Marin Solja\u010di\u0107 Thomas\u00a0Y Hou and Max Tegmark. 2024. Kan: Kolmogorov-arnold networks. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2404.19756 (2024)."},{"key":"e_1_3_3_1_11_2","unstructured":"Moein E. Samadi Younes Muller and Andreas Schuppert. 2024. Smooth Kolmogorov Arnold networks enabling structural knowledge representation. (2024)."},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"crossref","unstructured":"Hadrien Montanelli and Haizhao Yang. 2020. Error bounds for deep ReLU networks using the Kolmogorov\u2013Arnold superposition theorem. Neural Networks 129 (9 2020) 1\u20136.","DOI":"10.1016\/j.neunet.2019.12.013"},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICME55011.2023.00330"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"crossref","unstructured":"Andrew Polar and Michael Poluektov. 2021. A deep machine learning algorithm for construction of the Kolmogorov\u2013Arnold representation. Engineering Applications of Artificial Intelligence 99 (2021) 104137.","DOI":"10.1016\/j.engappai.2020.104137"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"crossref","unstructured":"Johannes Schmidt-Hieber. 2021. The Kolmogorov\u2013Arnold representation theorem revisited. Neural Networks 137 (5 2021) 119\u2013126.","DOI":"10.1016\/j.neunet.2021.01.020"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"publisher","unstructured":"Johannes Schmidt-Hieber. 2021. The Kolmogorov-Arnold representation theorem revisited. Neural networks : the official journal of the International Neural Network Society 137 (2021) 119\u2013126. 10.1016\/j.neunet.2021.01.020","DOI":"10.1016\/j.neunet.2021.01.020"},{"key":"e_1_3_3_1_17_2","unstructured":"John Smith and Emily Johnson. 2021. Advances in Convolutional Neural Networks for Image Classification. Journal of Machine Learning Research 22 1 (2021) 45\u201367."},{"key":"e_1_3_3_1_18_2","unstructured":"SS Sidharth and R. Gokul. 2024. Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation. (2024)."},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","unstructured":"Guangting Wang Yucheng Zhao Chuanxin Tang Chong Luo and Wenjun Zeng. 2022. When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism. AAAI 36 2 (2022) 2423\u20132430. 10.1609\/aaai.v36i2.20142","DOI":"10.1609\/aaai.v36i2.20142"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"crossref","unstructured":"Li Wang and Wei Zhang. 2023. Theoretical Foundations and Applications of Deep Learning in Computer Vision. International Journal of Computer Vision 89 3 (2023) 201\u2013219.","DOI":"10.1201\/9781003348689-10"},{"key":"e_1_3_3_1_21_2","unstructured":"Ziming Liu Yixuan Wang Sachin Vaidya Fabian Ruehle James Halverson Marin Solja\u010di\u0107 Thomas Y. Hou and Max Tegmark. 2024. KAN: Kolmogorov-Arnold Networks. (2024)."}],"event":{"name":"AIMLSystems 2024: The 4th International Conference on AI-ML Systems","location":"Baton Rouge Louisiana USA","acronym":"AIMLSystems 2024"},"container-title":["Proceedings of the 4th International Conference on AI-ML Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3703412.3703427","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3703412.3703427","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:18:07Z","timestamp":1750295887000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3703412.3703427"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,8]]},"references-count":20,"alternative-id":["10.1145\/3703412.3703427","10.1145\/3703412"],"URL":"https:\/\/doi.org\/10.1145\/3703412.3703427","relation":{},"subject":[],"published":{"date-parts":[[2024,10,8]]},"assertion":[{"value":"2025-03-05","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}